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Best Online Doctorates in Artificial Intelligence: Top PhD Programs, Career Paths, and Salary

The best online PhD in Artificial Intelligence (AI) can get you a high-paying job at a tech company or an exciting position in a research institution. You don’t have to go to college on-campus to earn an online PhD in Artificial Intelligence. All you need is a laptop and a stable Internet connection.

Getting an artificial intelligence PhD online opens the door to many career options and improves your qualifications in the job market. Artificial intelligence jobs are well-paid and will continue to grow in importance in the years to come. Continue reading to learn more about the best PhD programs to help you narrow your school search and begin your doctoral studies.

Find your bootcamp match

Can you get a phd in artificial intelligence online.

Yes, you can get a PhD in Artificial Intelligence online. However, there aren’t many educational programs offering this online degree since AI is most commonly offered as a specialization area in doctoral programs in computer and data science. Additionally, many universities offer PhD degrees only on campus.

There are many online graduate degrees in machine learning, a subset of artificial intelligence. Additionally, there are several doctoral degrees available in big data, a fundamental tool for applied artificial intelligence technologies. You may want to consider including PhD Degrees in Data Science in your school search, as they offer well-structured curricula geared toward AI.

Is an Online PhD Respected?

Yes, an online PhD is respected. It’s a doctoral degree with academic equivalence to in-campus programs. Degree holders can access the same career opportunities and research positions in AI as on-campus graduates.

The respect from employers and research institutions for online PhD programs is mainly related to the reputation of the school, regardless of whether it’s an on-campus or online degree. Be sure to apply only to online PhD degrees from schools with official accreditation and that host relevant artificial intelligence research projects.

What Is the Best Online PhD Program in Artificial Intelligence?

The best online PhD program in artificial intelligence is the Doctor of Science in Computer Science from Aspen University. This entirely online doctoral program offers an excellent education in AI and is flexible and affordable for busy professionals and part-time students.

Why Aspen University Has the Best Online PhD Program in Artificial Intelligence

Aspen University has the best PhD program in artificial intelligence because it allows students to focus on their passion by choosing a capstone project of their interest within the branch of AI. With a total cost of $30,500, the Doctor of Science in Computer Science is the most affordable online doctoral program.

Students enrolled at Aspen University have up to ten years to complete the program at their own pace. Graduates from this program can join research teams in the public or private sectors to find and develop new applications for artificial intelligence and software engineering.

Best Online Master’s Degrees

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Online PhD in Artificial Intelligence Admission Requirements

The admission requirements for an online PhD in Artificial Intelligence vary considerably depending on the institution. For example, Capitol Technology University requires a master’s degree in a relevant field, two letters of recommendation, and a resume that shows five years of related work experience.

On the other hand, the PhD in Computer Science from Northcentral University only requires a master’s degree from an accredited institution. The online Doctor of Science in Computer Science from Aspen University requires applicants to be competent object oriented programming (OOP) developers, or they can take prerequisite courses to fulfill the requirement.

Some universities require GRE exam scores and personal statement essays, and all programs will require official transcripts of previous academic work. Prospective English as a second language (ESL) and international students will need to provide proof of English proficiency in the form of the Test of English as a Foreign Language (TOEFL) exam scores.

• Master’s degree in fields relevant to AI, computer science, or machine learning
• Resume showing relevant work experience
• GRE exam scores, depending on the school
• TOEFL exam or equivalent for ESL and international students
• Letters of recommendation
• Entrance essay or personal statement describing your research interests
• Interview by phone or in-person with a representative of the doctoral program, depending on the school

Best Online PhDs in Artificial Intelligence: Top Degree Program Details

Best Online PhDs in Artificial Intelligence: Top University Programs to Get a PhD in Artificial Intelligence Online

The top university programs to get a PhD in Artificial Intelligence online include Aspen University, Capitol Technology University, Colorado Technical University, Northcentral University, and the University of North Dakota. 

These schools offer the best online AI PhDs, which include PhDs in Artificial Intelligence and Big Data Analysis doctoral programs. Some online educational programs in computer science offer specialization courses in artificial intelligence and machine learning as part of their curricula.

Aspen University is a modern private institution with broad academic programs for distance learning. It has four schools offering online bachelor’s degrees and master’s and doctoral programs. Aspen has an open admission policy, and courses begin every two weeks. The university provides a self-paced approach to studying, and students have between two and ten years to complete any graduate degree.

Doctor of Science in Computer Science

The Doctor of Science in Computer Science program from the School of Business and Technology at Aspen University includes courses in artificial intelligence, the automata complexity theory, and computer ethics. Graduate students of this program will also have the opportunity to work on a research dissertation of their interest. 

Doctor of Science in Computer Science Overview

• Accreditation: Distance Education Accrediting Commission
• Program Length: 2 to 10 years (self-paced)
• Acceptance Rate: 100% (open admission policy)
• Tuition and Fees: $30,500

Doctor of Science in Computer Science Admission Requirements

• Demonstrate professional object oriented programming (OOP) skills
• Master’s degree 
• Official transcripts with a GPA of 3.0 or higher
• Statement of goals, indicating academic, professional, and personal goals

Capitol Technology University is a private university that was originally founded in 1927 to educate radio and electronics technicians. The university is home to the Space Operation Institute, which partners with NASA to train astronautical engineers. The university has just over 740 students in undergraduate and graduate STEM programs.

PhD in Artificial Intelligence

The PhD in Artificial Intelligence degree program aims to engineer computer systems that match the human brain’s decision-making processes. Students conduct unique research with the guidance of skilled academic supervisors. Students can graduate with a thesis or by publishing three articles in high-impact journals. Sixty credit hours are required to earn the degree.

PhD in Artificial Intelligence Overview

• Accreditation: Middle States Commission on Higher Education
• Program Length: 3 years
• Acceptance Rate: N/A
• Tuition: $933/credit

PhD in Artificial Intelligence Admission Requirements

• A master’s degree in a field relevant to artificial intelligence
• Official transcripts
• Online application and non-refundable application fee of $100
• A resume that demonstrates 5 years of related work experience
• Two recommendation forms 
• Personal essay on your technological expertise and how you are prepared to succeed in the program

Colorado Technical University (CTU) is a private university founded in 1965 to help veterans transition into civilian life. CTU is tech-oriented and offers over 80 undergraduate and graduate programs. The university prides itself on enabling US military personnel stationed overseas to take part in CTU’s numerous online learning options.

Doctorate in Big Data Analytics Online

This comprehensive program focuses on the fundamental theoretical, research, and field applications of AI. You will need 100 credit hours to complete this doctoral program , four of which correspond to participation in two in-campus symposia. The cost of the entire program is $64,640.

Doctorate in Big Data Analytics Online Overview

• Accreditation: Higher Learning Commission
• Tuition and Fees: $64,640 total

Doctorate in Big Data Analytics Online Admission Requirements

• Conversation with an admissions advisor to discuss your academic goals
• Interview by phone or in-person with a department representative
• Entrance essay
• Accredited bachelor’s degree

Northcentral University is an accredited, private online school founded in 1996 and based in San Diego, California. All of NCU’s programs are offered online, and the school has over 10,000 online students. The school does not require GRE, GMAT, or any standardized test scores for admission, and the doctoral faculty offers one-to-one career counseling.

PhD in Computer Science 

You’ll need 60 credit hours to complete the PhD in Computer Science program online at NCU. The total estimated cost of the program is $68,560 and can be completed in 3 years. The curriculum is designed for graduate students to explore theoretical concepts and gain relevant skills in their preferred areas of expertise, including AI, data mining , and cyber security. 

PhD in Computer Science Overview

• Tuition and Fees: $68,560 total or $3,282/credit

PhD in Computer Science Admission Requirements

• Master’s degree from a regionally or nationally accredited academic institution
• Online application

The University of North Dakota (UND) is a public research university that was founded in 1883 and enrolls over 13,000 graduate and undergraduate students. UND is a leading school in aviation, space, and unmanned aircraft education and offers more than 140 graduate degree programs. 

Students enrolled in the PhD in Computer Science program can take specialization courses in AI and machine learning. The comprehensive program requires 90 credits and explores topics such as bioinformatics, compiler design, software engineering , and the practical and theoretical frameworks of computer science. 

• Program Length: 4 to 5 years
• Tuition and Fees: $869/credit
• Master's Degree in Science or Engineering with an overall minimum GPA of 3.0
• Expertise in high-level programming languages and basic knowledge of data structures
• Basic skills in calculus, statistics, and linear algebra
• Online application and non-refundable application fee of $35
• Three letters of recommendation
• Statement of goals

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Online Artificial Intelligence PhD Graduation Rates: How Hard Is It to Complete an Online PhD Program in Artificial Intelligence?

It can be quite hard to complete an online PhD program in artificial intelligence. According to a study conducted by researchers from Nova Southeastern University, doctoral programs have average attrition rates of over 50 percent and up to 70 percent for online doctoral programs . PhD coursework can be demanding and highly time-consuming for nearly all programs.

Working closely with your academic advisor increases your chances of success and prevents disengagement, especially in online degree programs. An academic advisor will offer career counseling to help you tackle defeatist attitudes. To ensure completion, you should stay in communication with your advisor to make a plan with achievable milestones.

How Long Does It Take to Get a PhD in Artificial Intelligence Online?

It takes about three to five years to get a PhD in Artificial Intelligence online. Some programs take more than five years to complete the credit requirements and the doctoral thesis. Most online programs offer a flexible timeline to complete the degree requirements and are designed for people who are holding a job while they study.

Most programs offer one-to-one career counseling from the doctoral faculty to find solutions for students to allocate time and design strategies to complete the program. Students can pause their studies for set periods of time and resume their studies at a more convenient time for them.

How Hard Is an Online Doctorate in Artificial Intelligence?

An online doctorate in artificial intelligence can be quite hard. It requires good learning skills to complete three to four years of coursework. There is also a considerable financial commitment and long hours of doctoral-level readings and thesis work.

Not all the online PhD programs in artificial intelligence require a high-level education in computer science theory, math, or engineering. Some programs welcome students from any field because nearly every industry is finding new practical applications for AI.

Best PhD Programs

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What Courses Are in an Online Artificial Intelligence PhD Program?

The common courses in an online artificial intelligence PhD program include artificial intelligence research backgrounds, artificial intelligence research methodologies, and artificial intelligence future trends . Some programs also include machine learning, deep learning, and computer vision courses.

Main Areas of Study in an Artificial Intelligence PhD Program

• Machine learning
• Deep learning
• Machine vision
• Natural language processing

How Much Does Getting an Online Artificial Intelligence PhD Cost?

It costs $19,314 on average to get a PhD in Artificial Intelligence, according to the National Center for Education Statistics. The exact costs of the program vary according to the institution. However, this is an average figure, and tuition costs will vary significantly.

Some schools, like the University of North Dakota, allow you to transfer up to 30 credits from approved master’s degree programs. Private schools are typically more expensive than public universities, and some schools will charge more for out-of-state tuition. There are many private and public grants available for students in STEM doctoral programs.

How to Pay for an Online PhD Program in Artificial Intelligence

You can pay for an online PhD in Artificial Intelligence by getting scholarships, grants, loans, and employment or internship opportunities. The University of North Dakota offers positions with remote capabilities that don’t require an on-campus presence. You can also apply for a Direct PLUS Loan from the US Department of Education.

The Federal Student Aid office also offers several types of financial aid for students in graduate programs. Use the Federal Student Aid Estimator to learn how much financial aid you can get from the federal government.

How to Get an Online PhD for Free

You can’t get an online PhD for free. Some online colleges, like Northcentral University, offer a few full-tuition scholarships every semester for online master’s degrees and doctoral programs. The US military also offers full and partial scholarships for service members, their spouses, and children. It’s best to research the financial support options offered by the school.

What Is the Most Affordable Online PhD in Artificial Intelligence Degree Program?

The most affordable online PhD in Artificial Intelligence degree program is the Doctor of Science in Computer Science from Aspen University. The total cost for this doctoral degree is $30,500, consisting of $27,000 in tuition and $3,500 in fees.

Most Affordable Online PhD Programs in Artificial Intelligence: In Brief

Why You Should Get an Online PhD in Artificial Intelligence

You should get an online PhD in Artificial Intelligence because it is a great way to access better-paid positions and improve your relevance in the job market. With a PhD in AI, you can join skilled teams at companies that are developing new AI applications for every industry or choose to teach and do research in academia.

Top Reasons for Getting a PhD in Artificial Intelligence

• Job opportunities. With a PhD in Artificial Intelligence, you have greater opportunities in the job market. Many companies are creating new positions to integrate AI into their products and services. The demand for specialists in artificial intelligence is increasing, particularly for machine learning analysts and programmers.
• Higher salaries. Employees with expertise in AI are very valuable for employers, regardless of the type of industry. A doctoral degree in artificial intelligence shows that you have the highest level of education in AI and are qualified for positions that pay higher salaries.
• Research opportunities. A doctoral degree in artificial intelligence opens doors to postdoctoral programs and internships in the best AI research centers in the US. There is an increasing demand for AI researchers in public and private institutions, and the research skills gained in a PhD program will highly qualify you for these roles.
• New skills. During your academic journey in a doctoral program in artificial intelligence, you will develop technical skills that will be essential in the emerging AI workforce. These skills include the management of large data sets, natural language processing , and machine learning to improve process precision.

Best Master’s Degree Programs

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What Is the Difference Between an On-Campus Artificial Intelligence PhD and an Online PhD in Artificial Intelligence?

The difference between an on-campus artificial intelligence PhD and an online PhD in Artificial Intelligence is how the schools deliver the courses and the way you interact with faculty. The cost of online PhD programs in artificial intelligence is usually the same as on-campus programs. Online students don’t need to commute or pay campus-related fees.

On-campus programs enforce in-person learning, and students work with faculty and other students on campus to do relevant coursework and research. In an online program, all the relevant learning materials, like digital books, research articles, interactive activities, virtual labs, and discussion forums, are located on the school’s online learning platform.

Online PhD vs On-Campus PhD: Key Differences

• Convenience. With an online PhD program, you don’t need to waste time commuting. You can study from the comfort of your home at the time of your convenience. All the materials, including digital books, lectures, and readings, are located on the online learning platform.
• Affordability. Tuition costs are typically the same for both online and on-campus programs. However, with an online PhD program, you don’t have to pay on-campus related fees, like access to athletic facilities or parking.
• Flexible timelines. Most online PhD programs are designed for students who also hold jobs. Faculty and academic advisors will help you create a program timeline that doesn’t overwhelm you. Additionally, online PhD programs allow you to pause your studies and resume them according to your time availability.
• Location. All you need to complete an online PhD program is a computer and an Internet connection. You can bring your laptop to your workplace or complete your assignments while traveling the world. Many students of online PhD programs are military personnel stationed overseas.

How to Get a PhD in Artificial Intelligence Online: A Step-by-Step Guide

To get a PhD in Artificial Intelligence online, you’ll need to meet the degree requirements of your doctoral program. Your academic advisor can provide career counseling to create a strategy according to your time availability. You will earn your PhD degree after completing all the required credit hours and defending your dissertation.

The first step to obtaining your PhD degree is to prepare your documentation for the application process. This includes official transcripts, a resume, and the contact information of your references. Let your references know the admissions office will write or call them to validate their recommendation and prepare yourself for an interview with the program’s coordinator.

The program faculty will assign you an academic advisor who will provide you with academic counseling during your learning journey. You should work closely with them to set realistic and achievable benchmarks for your coursework. 

Your academic advisor will let you know when it's time to choose an area of specialization. You will then select the elective courses according to that specialization. Choose a specialization area according to your job interests after graduation. 

Most online PhD programs in artificial intelligence require you to complete between 60 and 100 credits. Some of the final credits correspond to your dissertation research. You will have to complete the coursework and write a doctoral dissertation with an original contribution.

The last step to earning your PhD in Artificial Intelligence is to present your final oral examination or dissertation defense. If your research represents an original contribution, and the school approves your publishable dissertation, the PhD degree will be yours.

Online PhD in Artificial Intelligence Salary and Job Outlook

The salary and job outlook for professionals with a doctoral degree in artificial intelligence are higher than average, with most salaries above $100,000 per year. There are several well-paid jobs in industries that are increasing the number of AI projects to develop new products and services.

What Can You Do With an Online Doctorate in Artificial Intelligence? 

With an online doctorate in artificial intelligence, you can get a job in AI , a rapidly growing field with new applications in nearly all industries. Tech and software companies include AI components in their programs and online services to gain a competitive advantage over traditional services.

There are many ways to learn artificial intelligence , but a doctoral degree makes you an expert in AI. With an online doctorate in artificial intelligence, you can apply for internships in AI-leading companies and participate in their algorithm development.

Best Jobs with a PhD in Artificial Intelligence

• Artificial Intelligence Specialist
• Machine Learning Engineer
• Research Engineer
• Technical Architect
• Data Scientist

Potential Careers With an Artificial Intelligence Degree

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What Is the Average Salary for an Online PhD Holder in Artificial Intelligence?

The average salary for someone with a PhD in Artificial Intelligence is $115,000 per year , according to PayScale. A machine learning engineer has an average annual salary of $112,709 , while a lecturer will earn an average yearly salary of $77,910 . Continue reading below for some of the top-paying jobs available in the field after graduation.

Highest-Paying Artificial Intelligence Jobs for PhD Grads

Best Artificial Intelligence Jobs for Online PhD Holders

The best artificial intelligence jobs for PhD holders include AI specialist and machine learning engineer. Those that work in this field usually deploy AI models to improve the accuracy and performance of information processes. These jobs require the use of deep learning, machine learning, and natural language processing methods.

Artificial intelligence specialists apply AI principles to find solutions to real-world problems that traditional computing approaches can’t solve. They work in interdisciplinary teams to apply AI components that improve the overall system performance. 

• Salary with an artificial intelligence PhD: $132,995
• Job Outlook: 22% job growth from 2020 to 2030
• Number of Jobs: 33,000
• Highest-Paying States: Oregon, Arizona, Texas, Massachusetts, and Washington

Machine learning engineers create and improve engines for processing vast amounts of data, also known as big data. By improving how machine learning models integrate additional sets of data, they increase the predictive capacities of an engine, for example.

• Salary with an artificial intelligence PhD: $124,800

Technical architects with AI expertise design computer networks that follow an AI-centered architecture. They incorporate cloud services into corporate networks, thereby increasing security and reducing costs associated with on-premises computing systems. They also design migration strategies to AI-based computer networks.

• Salary with an artificial intelligence PhD: $118,808
• Job Outlook: 5% job growth from 2020 to 2030
• Number of Jobs: 165,200
• Highest-Paying States: New Jersey, Rhode Island, Delaware, Virginia, and Maryland

Data scientists develop models for data management and processing. They use deep learning techniques to understand customers better and improve products and services with that insight. Algorithm development is one of the most important daily tasks of data scientists.

• Salary with an artificial intelligence PhD: $111,250
• Number of Jobs: 63,200
• Highest-Paying States: Washington, California, Delaware, New York, and New Jersey

Software developers implement artificial intelligent components into programs and online services. These AI components require software development for natural language processing, which is used for voice recognition. Software developers also code programs that use big data to provide accurate search results.

• Salary with an artificial intelligence PhD: $110,140
• Number of Jobs: 1,847,900
• Highest-Paying States: California, Washington, Maryland, New York, and Rhode Island

Is It Worth It to Do a PhD in Artificial Intelligence Online?

Yes, it is worth it to pursue a PhD in Artificial Intelligence online. While a doctoral degree program entails an important investment of time and money, the outcome is worth the effort. A PhD substantially improves your chances of increasing your income with a broader career potential.

Artificial intelligence is a fast-growing field for which all industries are finding new applications every day. An online PhD in Artificial Intelligence shows that you are an expert in AI and that you are qualified to apply for jobs that use artificial intelligence .

Additional Reading About Artificial Intelligence

[query_class_embed] https://careerkarma.com/blog/artificial-intelligence/ https://careerkarma.com/blog/best-artificial-intelligence-bachelors-degrees/ https://careerkarma.com/blog/best-artificial-intelligence-masters-degrees/

Online PhD in Artificial Intelligence FAQ

Anyone who wants to start a career in AI or machine learning can study artificial intelligence. Jobs for artificial intelligence specialists are well-paid and in high demand. You can earn an online degree in artificial intelligence or take an artificial intelligence bootcamp .

Today, artificial intelligence is used in most software-as-a-service (SAAS) applications. It is used in systems that create predictions using big data. AI applications are also found in voice recognition applications, navigation systems, and chatbot assistants.

Artificial intelligence matters because it is increasingly used to improve processes across all domains. Scientists use AI to find new drugs and create new materials. Companies use deep learning to understand their customers better and provide more accurate solutions.

Yes, artificial intelligence will create new jobs. Artificial intelligence engines are increasing their number of cognitive functions to solve problems faster than humans. Meanwhile, there is a growing demand for specialists to find new applications for AI.

About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication .

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Machine Learning - CMU

Phd program in machine learning.

Carnegie Mellon University's doctoral program in Machine Learning is designed to train students to become tomorrow's leaders through a combination of interdisciplinary coursework, hands-on applications, and cutting-edge research. Graduates of the Ph.D. program in Machine Learning will be uniquely positioned to pioneer new developments in the field, and to be leaders in both industry and academia.

Understanding the most effective ways of using the vast amounts of data that are now being stored is a significant challenge to society, and therefore to science and technology, as it seeks to obtain a return on the huge investment that is being made in computerization and data collection. Advances in the development of automated techniques for data analysis and decision making requires interdisciplinary work in areas such as machine learning algorithms and foundations, statistics, complexity theory, optimization, data mining, etc.

The Ph.D. Program in Machine Learning is for students who are interested in research in Machine Learning.  For questions and concerns, please   contact us .

The PhD program is a full-time in-person committment and is not offered on-line or part-time.

PhD Requirements

Requirements for the phd in machine learning.

• Completion of required courses , (6 Core Courses + 1 Elective)
• Mastery of proficiencies in Teaching and Presentation skills.
• Successful defense of a Ph.D. thesis.

Teaching Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

Research It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements In addition, students must follow all university policies and procedures .

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs): The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

• At least one MLD Core Faculty member
• At least one additional MLD Core or Affiliated Faculty member
• At least one External Member, usually meaning external to CMU
• A total of at least four members, including the advisor who is the committee chair

Financial Support

Application Information

For applicants applying in Fall 2024 for a start date of August 2025 in the Machine Learning PhD program, GRE Scores are OPTIONAL. The committee uses GRE scores to gauge quantitative skills, and to a lesser extent, also verbal skills.

Proof of English Language Proficiency If you will be studying on an F-1 or J-1 visa, and English is not a native language for you (native language…meaning spoken at home and from birth), we are required to formally evaluate your English proficiency. We require applicants who will be studying on an F-1 or J-1 visa, and for whom English is not a native language, to demonstrate English proficiency via one of these standardized tests: TOEFL (preferred), IELTS, or Duolingo.  We discourage the use of the "TOEFL ITP Plus for China," since speaking is not scored. We do not issue waivers for non-native speakers of English.   In particular, we do not issue waivers based on previous study at a U.S. high school, college, or university.  We also do not issue waivers based on previous study at an English-language high school, college, or university outside of the United States.  No amount of educational experience in English, regardless of which country it occurred in, will result in a test waiver.

Submit valid, recent scores:   If as described above you are required to submit proof of English proficiency, your TOEFL, IELTS or Duolingo test scores will be considered valid as follows: If you have not received a bachelor’s degree in the U.S., you will need to submit an English proficiency score no older than two years. (scores from exams taken before Sept. 1, 2023, will not be accepted.) If you are currently working on or have received a bachelor's and/or a master's degree in the U.S., you may submit an expired test score up to five years old. (scores from exams taken before Sept. 1, 2019, will not be accepted.)

Graduate Online Application

• Admissions application opens September 4, 2024
• Early Application Deadline – November 20, 2024 (3:00 p.m. EST)
• Final Application Deadline - December 11, 2024 (3:00 p.m. EST)

PhD in Artificial Intelligence

To enter the Doctor of Philosophy in Artificial Intelligence, you must apply online through the UGA  Graduate School web page . There is an application fee, which must be paid at the time the application is submitted.

There are several items which must be included in the application:

• Standardized test scores, including the GRE. 
• 3 letters of recommendation, preferably from university faculty and/or professional supervisors. We encourage you to submit the letters to the graduate school online as you complete the application process.
• A sample of scholarly writing, in English. This can be anything you've written but should give an accurate indication of your writing abilities. The writing sample can be a term paper, research report, journal article, published paper, college paper, etc.
• A completed  Application for Graduate Assistantship , if you are interested in receiving funding. 
• A Statement of Purpose.
• A Resume or Curriculum Vitae.

Further information on program admissions is found in the AI Institute Frequently Asked Questions (FAQ) . 

International Students should also review the links on the  Information for International Students  page for additional information relevant to the application process.

Graduate School Policies

University of Georgia Graduate School policies and requirements apply in addition to (and, in cases of conflict, take precedence over) those described here. It is essential that graduate students familiarize themselves with Graduate School policies, including minimum and continuous enrollment  and other policies contained in the Graduate School Bulletin.

Students should also familiarize themselves with Graduate School Dates and Deadlines relevant to the degree.

Degree Requirements

Students of the doctoral program must complete a minimum of 40 hours of graduate coursework and 6 hours of dissertation credit (for a total of 46 credit hours), pass a comprehensive examination, and write and defend a dissertation. In addition, the University requires that all first-year graduate students enroll in a 1-credit-hour GradFirst seminar . Each of these requirements is described in greater detail below.

The degree program is offered using an in-person format, and classes are in general scheduled for full-time students. There are currently no special provisions for part-time, online, or off-campus students. Students are expected to attend all meetings of classes for which they are registered.

Program of Study

The Program of Study must include a minimum of 40 hours of graduate course work and a minimum of 6 hours of dissertation credit. Of the 40 hours of graduate course work, at least 20 hours must be 8000-level or 9000-level hours.

Required Courses

The following courses must be completed unless specifically waived for students entering the program with a master’s degree in Artificial Intelligence or a related field, or for students with substantially related graduate course work. All waived credits may be replaced by an equal number of doctoral research or doctoral dissertation credits (ARTI 9000, Doctoral Research or ARTI 9300, Doctoral Dissertation). Substitutions must be approved for a particular student by that student's Advisory Committee and by the Graduate Coordinator.

• PHIL/LING 6510  Deductive Systems (3 hours)
• CSCI 6380  Data Mining (4 hours) or CSCI 8950  Machine Learning (4 hours)
• CSCI/PHIL 6550  Artificial Intelligence (3 hours)
• ARTI 6950  Faculty Research Seminar (1 hour)
• ARTI/PHIL 6340 Ethics and Artificial Intelligence (3 hours)

Elective Courses

In addition to the required courses above, at least 6 additional courses must be taken from Groups A and Group B below, subject to the following requirements. 

• At least 2 courses must be taken from Group A, from at least 2 areas.
• At least 2 courses must be taken from Group B, from at least 2 areas.
• At least 3 courses must be taken from a single area comprising the student’s chosen area of emphasis .

Since not all courses have the same number of credit hours, Ph.D. students may need to take additional graduate courses to complete the 40 hours.

AREA 1: Artificial Intelligence Methodologies

• CSCI 6560  Evolutionary Computing (4 hours)
• CSCI 8050  Knowledge Based Systems (4 hours)
• CSCI/PHIL 8650  Logic and Logic Programming (4 hours)
• CSCI 8920  Decision Making Under Uncertainty (4 hours)
• CSCI/ENGR 8940  Computational Intelligence (4 hours)
• CSCI/ARTI 8950  Machine Learning (4 hours)

AREA 2: Machine Learning and Data Science

• CSCI 6360  Data Science II (4 hours)
• CSCI 8360  Data Science Practicum (4 hours)
• CSCI 8945  Advanced Representation Learning (4 hours)
• CSCI 8955  Advanced Data Analytics (4 hours)
• CSCI 8960  Privacy-Preserving Data Analysis (4 hours)

AREA 3: Machine Vision and Robotics

• CSCI/ARTI 6530  Introduction to Robotics (4 hours)
• CSCI 6800  Human Computer Interaction (4 hours)
• CSCI 6850  Biomedical Image Analysis (4 hours)
• CSCI 8850  Advanced Biomedical Image Analysis (4 hours)
• CSCI 8820  Computer Vision and Pattern Recognition (4 hours)
• CSCI 8530  Advanced Topics in Robotics (4 hours)
• CSCI 8535  Multi Robot Systems (4 hours)

AREA 4: Cognitive Modeling and Logic

• PHIL/LING 6300  Philosophy of Language (3 hours)
• PHIL 6310  Philosophy of Mind (3 hours)
• PHIL/LING 6520  Model Theory (3 hours)
• PHIL 8310  Seminar in Philosophy of Mind (max of 3 hours)
• PHIL 8500  Seminar in Problems of Logic (max of 3 hours)
• PHIL 8600  Seminar in Metaphysics (max of 3 hours)
• PHIL 8610  Epistemology (max of 3 hours)
• PSYC 6100  Cognitive Psychology (3 hours)
• PSYC 8240  Judgment and Decision Making (3 hours)
• CSCI 6860  Computational Neuroscience (4 hours)

AREA 5: Language and Computation

• ENGL 6885  Introduction to Humanities Computing (3 hours)
• LING 6021  Phonetics and Phonology (3 hours)
• LING 6080  Language and Complex Systems (3 hours)
• LING 6570  Natural Language Processing (3 hours)
• LING 8150  Generative Syntax (3 hours)
• LING 8580  Seminar in Computational Linguistics (3 hours)

AREA 6: Artificial Intelligence Applications

• ELEE 6280  Introduction to Robotics Engineering (3 hours)
• ENGL 6826  Style: Language, Genre, Cognition (3 hours)
• ENGL/LING 6885  Introduction to Humanities Computing (3 hours)
• FORS 8450  Advanced Forest Planning and Harvest Scheduling (3 hours)
• INFO 8000  Foundations of Informatics for Research and Practice
• MIST 7770  Business Intelligence (3 hours)

Students may under special circumstances use up to 6 hours from the following list to apply towards the Electives group requirement. 

• ARTI 8800  Directed Readings in Artificial Intelligence
• ARTI 8000  Topics in Artificial Intelligence

Other courses may be substituted for those on the Electives lists, provided the subject matter of the course is sufficiently related to artificial intelligence and consistent with the educational objectives of the Ph.D. degree program. Substitutions can be made only with the permission of the student's Advisory Committee and the Graduate Coordinator.

In addition to the specific PhD program requirements, all first-year UGA graduate students must enroll in a 1 credit-hour GRSC 7001 (GradFIRST) seminar which provides foundational training in research, scholarship, and professional development. Students may enroll in a section offered by any department, but it is recommended that they enroll in a section offered by AI Faculty Fellows for AI students. More information is available at the  Graduate School website .

Core Competency

Core competency must be exhibited by each student and certified by the student’s advisory committee. This takes the form of achievement in the required courses of the curriculum. Students entering the Ph.D. program with a previous graduate degree sufficient to cover this basic knowledge will need to work with their advisory committee to certify their core competency. Students entering the Ph.D. program without sufficient graduate background to certify core competency must take at least three of the required courses, and then pursue certification with their advisory committee. A grade average of at least 3.56 (e.g., A-, A-, B+) must be achieved for three required courses (excluding ARTI 6950). Students below this average may take the fourth required course and achieve a grade average of at least 3.32 (e.g., A-, B+, B+, B).

Core competency is certified by the unanimous approval of the student's Advisory Committee as well as the approval by the Graduate Coordinator. Students are strongly encouraged to meet the core competency requirement within their first three enrolled academic semesters (excluding summer semester).  Core Competency Certification must be completed before approval of the Final Program of Study.

Comprehensive Examination

Each student of the doctoral program must pass a Ph.D. Comprehensive Examination covering the student's advanced coursework. The examination consists of a written part and an oral part. Students have at most two attempts to pass the written part. The oral part may not be attempted unless the written part has been passed.

Admission to Candidacy

The student is responsible for initiating an application for admission to candidacy once all requirements, except the dissertation prospectus and the dissertation, have been completed.

Dissertation and Dissertation Credit Hours

In addition to the coursework and comprehensive examination, every student must conduct research in artificial intelligence under the direction of an advisory committee and report the results of his or her research in a dissertation acceptable to the Graduate School. The dissertation must represent originality in research, independent thinking, scholarly ability, and technical mastery of a field of study. The dissertation must also demonstrate competent style and organization. While working on his/her dissertation, the student must enroll for a minimum of 6 credit hours of ARTI 9300 Doctoral Dissertation spread over at least 2 semesters.

Advisory Committee

Before the end of the third semester, each student admitted into the program should approach relevant faculty members and form an advisory committee. Until the committee is formed, the student will be advised by the graduate coordinator. The committee consists of a major professor and two other faculty members, as follows:

• The major professor and at least one other member must be full members of the Graduate Program Faculty.
• The major professor and at least one other member must be Institute for Artificial Intelligence Faculty Fellows.

Deviations from the 3-member advisory committee structure, including having more members, are in some cases permitted but must conform to Graduate School policies. 

The major professor and advisory committee shall guide the student in planning the dissertation.  The committee shall agree upon, document, and communicate expectations for the dissertation. These expectations may include publication or submission requirements, but, should not exceed reasonable expectations for the given research domain. During the planning stage, the student will prepare a dissertation prospectus in the form of a detailed written dissertation proposal. It should clearly define the problem to be addressed, critique the current state-of-the-art, and explain the contributions to research expected by the dissertation work. When the major professor certifies that the dissertation prospectus is satisfactory, it must be formally considered by the advisory committee in a meeting with the student. This formal consideration may not take the place of the comprehensive oral examination.

Approval of the dissertation prospectus signifies that members of the advisory committee believe that it proposes a satisfactory research study. Approval of the prospectus requires the agreement of the advisory committee with no more than one dissenting vote as evidenced by their signing an appropriate form to be filed with the graduate coordinator’s office.  

Graduation Requirements - Forms and Timeline

Before the end of the third semester in residence, a student must begin submitting to the Graduate School, through the graduate coordinator, the following forms: (i) a Preliminary Program of Study Form and (ii) an Advisory Committee Form. The Program of Study Form indicates how and when degree requirements will be met and must be formulated in consultation with the student's major professor. An Application for Graduation Form must also be submitted directly to the Graduate School. Forms and Timing must be submitted as follows:

• Advisory Committee Form (G130)—end of third semester
• Core Competency Form (Internal to IAI)—beginning of fourth semester
• Preliminary Doctoral Program of Study Form—Fourth semester
• Final Program of Study Form (G138)—before Comprehensive Examination
• Application for Admission to Candidacy (G162)—after Comprehensive Examination
• Application for Graduation Form (on Athena)—beginning of last semester
• Approval Form for Doctoral Dissertation (G164)—last semester
• ETD Submission Approval Form (G129)—last semester

Students should frequently check the Graduate School Dates and Deadlines webpage to ensure that all necessary forms are completed in a timely manner.

Student Handbook

Additional information on degree requirements and AI Institute policies can be found in the AI Student Handbook .

For information regarding the graduate programs in IAI, please contact: 

Evette Dunbar [email protected] Boyd GSRC, Room 516 706-542-0358

We appreciate your financial support. Your gift is important to us and helps support critical opportunities for students and faculty alike, including lectures, travel support, and any number of educational events that augment the classroom experience.  Click here to learn more about giving .

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Stanford Online

Artificial intelligence professional program.

Stanford School of Engineering

Per course $1,750 USD

10 weeks per course, 10-15 hours per week

Get Started

Artificial intelligence is transforming the world and helping organizations of all sizes grow, innovate, and make smarter decisions. The Artificial Intelligence Professional Program will equip you with knowledge of the principles, tools, techniques, and technologies driving this transformation. This online program provides rigorous coverage of the most important topics in modern artificial intelligence, including:

Machine Learning

• Deep Learning
• Natural Language Processing and Understanding
• Supervised and Unsupervised Learning

Reinforcement Learning

• Graph Neural Networks (GNNs)
• Multi-Task and Meta-Learning

The courses will equip you with the skills and confidence to:

• Build your own AI models and algorithms without the constraints of off-the-shelf solutions.
• Innovate and create new models, tools, and algorithms to tackle real-world challenges in AI.
• Effectively debug your code.
• Fine-tune and optimize model parameters for better results.
• Evaluate performance of AI models accurately.
• Implement generative language models.
• Perform few-shot and zero-shot learning with pre-trained language models.
• Understand research results and conduct your own research in the field.

Artificial Intelligence Professional Program FAQs

What you can expect

What you need to get started

Prior to enrolling in your first course, you must complete a short application (15-20 minutes). The application allows you to share more about your interest in joining, as well as verify that you meet the prerequisite requirements needed to make the most of the experience:

• Proficiency in Python: Coding assignments will be in Python. Some assignments will require familiarity with basic Linux command line workflows.
• College Calculus and Linear Algebra: You should be comfortable taking (multivariable) derivatives and understand matrix/vector notation and operations.
• Probability Theory: You should be familiar with basic probability distributions (Continuous, Gaussian, Bernoulli, etc.) and be able to define concepts for both continuous and discrete random variables: Expectation, independence, probability distribution functions, and cumulative distribution functions.

NOT SURE IF THIS PROGRAM IS RIGHT FOR YOU?

Learn about the differences between the graduate and professional AI Programs .

• Preview Image
• Course/Course #
• Time Commitment
• Availability

Natural Language Processing with Deep Learning

• Sep 16 - Nov 24, 2024

Machine Learning with Graphs

• Oct 7 - Dec 15, 2024

• Nov 4, 2024 - Jan 26, 2025

• Nov 11, 2024 - Feb 2, 2025

Deep Multi-Task and Meta Learning

• Jan 20 - Mar 30, 2025

Deep Generative Models

• Jan 27 - Apr 6, 2025

Natural Language Understanding

• Mar 3 - May 11, 2025

Flexible Enrollment Options

Individual enrollments.

$1,750 per course

Courses are online and the pace is set by the instructor. You will be part of a group of learners going through the course together. You will have scheduled assignments to apply what you've learned and will receive direct feedback from course facilitators.

Groups and Teams

Special Pricing

Have a group of five or more? Enroll as a group and learn together! By participating together, your group will develop a shared knowledge, language, and mindset to tackle challenges ahead. We can advise you on the best options to meet your organization’s training and development goals.

What You'll Earn

You’ll earn a Stanford Professional Certificate in Artificial Intelligence when you successfully complete either:

• Three courses in the AI professional education program, OR
• Two courses in the AI professional education program AND one course in the AI Graduate Program.

Your blockchain-verified digital certificate will allow you to showcase your achievements on LinkedIn and other platforms, validate credentials with employers, and highlight your expertise.

Academic Director

Christopher Manning

Thomas M. Siebel Professor of Machine Learning

Computer Science

Christopher Manning is a Professor of Computer Science and Linguistics at Stanford University and Director of the Stanford Artificial Intelligence Laboratory. He works on software that can intelligently process, understand, and generate human language material. He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, neural network dependency parsing, the GloVe model of word vectors, neural machine translation, question answering, and deep language understanding. He also focuses on computational linguistic approaches to parsing, robust textual inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning is an ACM Fellow, a AAAI Fellow, an ACL Fellow, and a Past President of ACL. He has coauthored leading textbooks on statistical natural language processing and information retrieval. He is a member of the Stanford NLP group (@stanfordnlp) and manages development of the Stanford CoreNLP software.

Teaching Team

Emma Brunskill

Associate Professor

Emma Brunskill is an Assistant Professor at Stanford University. Her goal is to increase human potential through advancing interactive machine learning. Revolutions in storage and computation have made it easy to capture and react to sequences of decisions made and their outcomes. Simultaneously, due to the rise of chronic health conditions, and demand for educated workers, there is an urgent need for more scalable solutions to assist people to reach their full potential. Interactive machine learning systems could be a key part of the solution. To enable this, her lab's work spans from advancing theoretical understanding of reinforcement learning, to developing new self-optimizing tutoring systems that they test with learners and in the classroom. Their applications focus on education since education can radically transform the opportunities available to an individual.

Stefano Ermon

Stefano Ermon is an Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment. His research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.

Chelsea Finn

Assistant Professor

Chelsea Finn is an Assistant Professor in the Computer Science Department at Stanford University. Her lab, IRIS, studies intelligence through robotic interaction at scale, and is affiliated with Stanford Artificial Intelligence Lab (SAIL) and the Statistical ML Group. She is interested in how algorithms can enable machines to acquire more general notions of intelligence through learning and interaction, allowing them to autonomously learn a variety of complex sensorimotor skills in real-world settings.

Jure Leskovec

Jure Leskovec is an Associate Professor of Computer Science at Stanford University. Leskovec's research focuses on the analyzing and modeling of large social and information networks as the study of phenomena across the social, technological, and natural worlds. He focuses on statistical modeling of network structure, network evolution, and spread of information, influence and viruses over networks. Problems he investigates are motivated by large scale data, the Web and other on-line media. He also does work on text mining and applications of machine learning.

Tengyu Ma is an Assistant Professor of Computer Science and Statistics at Stanford University. His research interests broadly include topics in machine learning and algorithms, such as non-convex optimization, deep learning and its theory, reinforcement learning, representation learning, distributed optimization, convex relaxation (e.g. sum of squares hierarchy), and high-dimensional statistics. He received my Ph.D. from the Computer Science Department at Princeton University where he was advised by Professor Sanjeev Arora. As an undergrad, Tengyu Ma studied at Andrew Chi-Chih Yao's CS pilot class at Tsinghua University.

Christopher Potts

Linguistics

Christopher Potts is a Professor of Linguistics and, by courtesy, of Computer Science and the Director of The Center for the Study of Language and Information (CSLI). In his research, he uses computational methods to explore how emotion is expressed in language and how linguistic production and interpretation are influenced by the context of utterance. He is the author of the 2005 book The Logic of Conventional Implicatures as well as numerous scholarly papers in computational and theoretical linguistics.

Christopher Ré

Christopher (Chris) Ré is an Associate Professor in the Department of Computer Science at Stanford University in the InfoLab who is affiliated with the Statistical Machine Learning Group, Pervasive Parallelism Lab, and Stanford AI Lab. His work's goal is to enable users and developers to build applications that more deeply understand and exploit data. His contributions span database theory, database systems, and machine learning, and his work has won best paper at a premier venue in each area, respectively, at PODS 2012, SIGMOD 2014, and ICML 2016. In addition, work from his group has been incorporated into major scientific and humanitarian efforts, including the IceCube neutrino detector, PaleoDeepDive and MEMEX in the fight against human trafficking, and into commercial products from major web and enterprise companies. He cofounded a company, based on his research, that was acquired by Apple in 2017. He received a SIGMOD Dissertation Award in 2010, an NSF CAREER Award in 2011, an Alfred P. Sloan Fellowship in 2013, a Moore Data Driven Investigator Award in 2014, the VLDB early Career Award in 2015, the MacArthur Foundation Fellowship in 2015, and an Okawa Research Grant in 2016.

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We have 6 Artificial Intelligence (distance learning) PhD Projects, Programmes & Scholarships in the UK

Computer Science

United Kingdom

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Artificial Intelligence (distance learning) PhD Projects, Programmes & Scholarships in the UK

Adaptive multi-access interoperable communication fabric for tinyedge, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Funded PhD Project (UK Students Only)

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

Large Language Models in Intelligent Robotic Systems for Environment Clean Up

Developing advanced machine learning model for an additively manufactured soft robotic hand: achieving human-like dexterity, funded phd project (students worldwide).

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Automated analysis of qualitative data using AI for patient safety

Fully-funded phd studentship in automated beta-emitting radioisotope identification and monitoring in boreholes, computational light microscopy — making the invisible visible.

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Ph.D. in Computer Science

Gain vital expertise to lead and innovate with the help of invaluable "practice experience" in a fast-paced, real-world environment.

Through critical and logical thinking, you’ll gain the essential knowledge and experience needed to become highly proficient in the use of today’s leading computing platforms and techniques.

Why earn a Ph.D. in computer science?

If you're an international student, refer to the international application process for deadlines.

Scientists and engineers in every industry rely on high-performance technology and large data sets, requiring experts that can help harness the latest sophisticated computing power to solve real-world problems.

With this graduate program, you'll:

• Get essential "practice experience" to help solve real-world problems and challenges through computational technology
• Develop the knowledge and skills that will prepare you to lead or support research in any technical career that relies on computer science.
• Develop your logic and critical-thinking skills to help solve today's most pressing scientific and engineering challenges.
• Choose from computation clusters focused on specialized computing system or methods, and application clusters for exposure to specific scientific disciplines.
• Work with practitioners in a variety of disciplines served by computer science .

On-Campus or Online Ph.D. in Computer Science

Benefit from strong departmental proficiencies in artificial intelligence, compiler design, database, networks, operating systems, graphics, simulation, software engineering, and theoretical computer science.

Shape the future of transportation. UND’s Transportation Technology Research Initiative is using autonomous systems to develop and maintain a modern transportation system.

Advance your technology skills with a curriculum that encourages a formal, abstract, theoretical and practical approach to the study of computer science.

Gain access to on-campus computer power: two computer labs, a set of diverse servers and a high-performance computing (HPC) system.  The supercomputer at UND runs on the HPE Apollo 6500 Gen10 system, purpose-built for HPC and a leading platform for deep learning. 

UND is a leader in big data expertise. We are the lead institution in a multi-university project for digital agriculture, funded by the National Science Foundation . And we  co-lead another NSF project to determine industry and academic computational needs in the Midwest.

Study at a Carnegie Doctoral Research Institution ranked #151 by the NSF. Students are an integral part of UND research.

What can I do with a Ph.D. in computer science?

Anticipated job growth for computer and information research scientists through 2032

U.S. Bureau of Labor Statistics

Median annual salary for computer and information research scientists, 2023

Graduates of the Computer Science Ph.D. program have dynamic career paths with titles such as:  

• Software engineer and developer
• Computational scientist
• Data science engineer
• Research scientists (technology companies and universities)

Because technology systems are so essential today, UND graduates can expect career opportunities across a range of industries. A small sampling of top industries needing advanced scientific computing skills include:

• Atmospheric science
• Bioinformatics
• Communications
• Engineering and science
• High tech (hardware)
• Renewable energy
• Scientific and medical research (private and university-level)
• Software engineering and design

Ph.D. in Computer Science Courses

CSCI 515. Data Engineering and Management. 3 Credits.

This course studies theoretical and applied research issues related to data engineering, management, and science. Topics will reflect state-of-the-art and state-of-the-practice activities in the field. The course focuses on well-defined theoretical results and empirical studies that have potential impact on data acquisition, analysis, indexing, management, mining, retrieval, and storage. Prerequisite: CSCI 513 . S, even years.

CSCI 543. Machine Learning. 3 Credits.

An introductory course in machine learning for data science. Topics include the learning algorithms of a Bayesian network, neural network, parametric/non-parametric methods, kernel machine, support-vector machine, etc. for regression, classification, clustering, dimensionality reduction, etc. Prerequisite: CSCI 365 or CSCI 384 . F, odd years.

CSCI 567. Secure Software Engineering. 3 Credits.

This course covers software engineering principles and techniques used in the development life-cycle of cyber secure systems. Topics covered include, the characteristics of secure software, the role of security in the development life-cycle, designing secure software, and best-practices in secure programming and testing. Study includes review of industrial standards for secure software system engineering. Prerequisite: EE 601 , EE 602 , and admission to the MS Cyber Security Program. SS.

CSCI 554. Applications in AI/Computational Intelligence. 3 Credits.

A continuous study of the computational paradigms of Soft Computing in the field of Computational Intelligence. The topics include the applications of the various soft computing techniques in Computational Intelligence as well as more evolutionary algorithms in Swarm Intelligence. Prerequisite: CSCI 544 . F, even years.

CSCI 555. Computer Networks. 3 Credits.

A study of new and developing network architectures and communication protocols. Broadband technologies will be considered including BISDN, ATM networks, and other high-speed networks. Prerequisite: CSCI 327 .

CSCI 557. Computer Forensics. 3 Credits.

An overview of the techniques to detect and assess the level of penetration of a security breach. Topics include forensic science in the cyber domain, laws and ethics of forensic activities, digital evidence, methods of forensic investigation, and forensic procedures in a variety of operating systems and network configurations. Prerequisite: EE 602 , or approval of the department, and admission to the MS program in Cyber Security. S.

Online Computer Science Ph.D.

best online graduate programs

best online college in North Dakota

Intelligent

UND's online Ph.D. in Computer Science is fully online. You never have to come to campus. You'll take a combination of synchronous and asynchronous online computer science courses. 

Affordable Online Colleges

UND is one of the most affordable online colleges in the region. For this program, we offer the same online tuition rates regardless of your legal residency. Compare and you’ll see UND is lower cost than similar four-year doctoral universities.

Top-Tier Online Computer Science Ph.D.

Over a third of UND's student population is exclusively online; plus, more take a combination of online and on campus classes. You can feel reassured knowing you won't be alone in your online learning journey and you'll have resources and services tailored to your needs. No matter how you customize your online experience, you’ll get the same top-quality education as any other on campus student.

• Same degree:  All online programs are fully accredited by the Higher Learning Commission (HLC) . Your transcript and diploma are exactly the same as our on-campus students.
• Same classes: You’ll take courses from UND professors, start and end the semesters at the same time and take the same classes as a student on campus.
• Real interaction:  You can ask questions, get feedback and regularly connect with your professors, peers and professionals in the field.
• Your own academic advisor:  As an invaluable go-to, they’re focused on you, your personal success and your future career.
• Free online tutoring:  We're here to help you one-on-one at no cost. Plus, get access to a variety of self-help online study resources.
• Unlimited academic coaching:  Need support to achieve your academic goals or feeling stumped by a tough course? We'll help with everything from stress and time management to improving your memory to achieve higher test scores.
• Full online access: Dig into virtual research at UND's libraries. Improve your writing skills with online help from the UND Writing Center. Get online access to career services, veteran and military services, financial services and more.
• 24/7 technical support:  UND provides free computer, email and other technical support for all online students.
• Networking opportunities: Our significant online student population means you’ll have a large pool of peers to connect with. UND has numerous online events and activities to keep you connected.

Best Online College

Our high alumni salaries and job placement rates, with affordable online tuition rates make UND a best-value university for online education. UND's breadth of online programs rivals all other nonprofit universities in the Upper Midwest making UND one of the best online schools in the region.

UND ranks among the best online colleges in the nation for:

• Affordability
• Student satisfaction (retention rate)
• Academic quality (4-year graduate rate)
• Student outcomes (20-year return on investment per Payscale.com)

Leaders in Computer Science

As a leader of Big Data, UND's goal is to make things more efficient, more effective and safer for North Dakotans.

Check out the faculty you'll work with at UND or discover additional education opportunities.

• School of Electrical Engineering & Computer Science
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Discover more about postgraduate research

PhD Artificial Intelligence

Year of entry: 2025

• View full page

The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).

For more information about applications, please visit the CDT in AI for Decision Making in Complex Systems website .

Full entry requirements

Please visit the CDT in AI for Decision Making in Complex Systems website for more information about applications.

Programme options

Programme overview

Please note: We are only accepting applications for PhD in Artificial Intelligence through the Centre for Doctoral Training (CDT) in AI for Decision Making in Complex Systems.

The Centre for Doctoral Training (CDT) in AI for Decision Making in Complex Systems is a 4-year programme that will educate the next generation of AI researchers to develop and deploy new machine learning models that can efficiently cope with uncertainty in complex systems.

Bringing together researchers in machine learning from the universities of Manchester and Cambridge, the CDT will be grounded in the research areas of physics and astronomy, engineering, biology, and material science, as well as a cross-cutting theme of using AI to increase business productivity, ultimately applying the research to real-world scenarios.

For more information, visit the CDT in AI for Decision Making in Complex Systems website .

Visit our Events and Opportunities page to find out more about upcoming open days and webinars.

Please visit the CDT in AI for Decision Making in Complex Systems website for more information about fees and funding.

Contact details

Programmes in related subject areas.

Use the links below to view lists of programmes in related subject areas.

• Computer Science

Entry requirements

Academic entry qualification overview, application and selection, how to apply, interview requirements, programme details, programme description.

The Centre for Doctoral Training (CDT) in AI for Decision Making in Complex Systems is a 4-year programme that will educate the next generation of AI researchers to develop and deploy new machine learning models that can efficiently cope with uncertainty in complex systems. Bringing together researchers in machine learning from the universities of Manchester and Cambridge, the CDT will be grounded in the research areas of physics and astronomy, engineering, biology, and material science, as well as a cross-cutting theme of using AI to increase business productivity, ultimately applying the research to real-world scenarios.

For more information, please visit the CDT in AI for Decision Making in Complex Systems website .

Special features

Scholarships and bursaries.

For more information about funding, please visit the CDT in AI for Decision Making in Complex Systems website .

Disability support

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Accounting and finance.

Find out about the University of Bristol's PhD in Accounting and Finance, including entry requirements, supervisors and research groups.

Advanced Quantitative Methods

Find out about the University of Bristol's PhD in Advanced Quantitative Methods, including entry requirements, supervisors and research groups.

Aerosol Science

Find out about the University of Bristol's PhD in Aerosol Science, including entry requirements, supervisors and research groups.

Aerospace Engineering

Find out about the University of Bristol's PhD in Aerospace Engineering, including entry requirements, supervisors and research groups.

Anthropology and Archaeology

Find out about the University of Bristol's PhD in Anthropology and Archaeology, including entry requirements, supervisors and research groups.

Biochemistry

Find out about the University of Bristol's PhD in Biochemistry, including entry requirements, supervisors and research groups.

Biological Sciences

Find out about the University of Bristol's PhD in Biological Sciences, including entry requirements, supervisors and research groups.

Cellular and Molecular Medicine

Find out about the University of Bristol's PhD in Cellular and Molecular Medicine, including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in Chemistry, including entry requirements, supervisors and research groups.

Civil Engineering

Find out about the University of Bristol's PhD in Civil Engineering, including entry requirements, supervisors and research groups.

Classics and Ancient History

Find out about the University of Bristol's PhD in Classics and Ancient History, including entry requirements, supervisors and research groups.

Clinical Conscious Sedation and Anxiety Management

Comparative literatures and cultures.

Find out about the University of Bristol's PhD and MPhil in Comparative Literatures and Cultures, including structure and supervisors.

Computer Science

Find out about the University of Bristol's PhD in Computer Science, including entry requirements, career prospects and research groups.

Creative Writing

Find out about the University of Bristol's PhD in Creative Writing, including entry requirements, supervisiors and research groups.

Cyber Security (Cyber Secure Everywhere)

Dds orthodontics.

Find out about the University of Bristol's Orthodontics Doctorate in Dental Surgery (DDS) research degree, including career prospects and supervisors.

DEdPsy Educational Psychology

Find out about the University of Bristol's Doctor of Educational Psychology (DEdPsy) research degree, including career prospects and supervisors.

Disability Studies

Find out about the University of Bristol's PhD in Disability Studies, including entry requirements, career prospects and research groups.

Dynamic Molecular Cell Biology (Wellcome Trust)

Find out about the University of Bristol's PhD in Dynamic Molecular Cell Biology, fully funded by the Wellcome Trust for UK students.

Earth Sciences

Find out about the University of Bristol's PhD in Earth Sciences, including entry requirements, supervisiors and research groups.

East Asian Studies

Find out about the University of Bristol's PhD in East Asian Studies, including entry requirements and key themes.

Find out about the University of Bristol's PhD in Economics, including entry requirements, supervisiors and research groups.

EdD Education: Learning, Leadership and Policy

Find out about the University of Bristol's EdD in Education: Learning, Leadership and Policy, including entry requirements, career prospects and research groups.

Find out about the University of Bristol's PhD in Education, including entry requirements, career prospects and research groups.

Electrical and Electronic Engineering

Find out about the University of Bristol's PhD in Electrical and Electronic Engineering, including entry requirements and research groups.

Engineering Biology

Engineering mathematics.

Find out about the University of Bristol's PhD in Engineering Mathematics, including entry requirements, career prospects and research groups.

English Literature

Find out about the University of Bristol's PhD in English Literature, including entry requirements, supervisors and research groups.

Exercise, Nutrition and Health

Find out about the University of Bristol's PhD in Exercise, Nutrition and Health, including entry requirements, supervisors and research groups.

Film and Television

Find out about the University of Bristol's PhD in Film and Television, including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in French, including entry requirements, supervisors and research groups.

Geographical Sciences (Human Geography)

Find out about the University of Bristol's PhD in Geographical Sciences (Human Geography), including entry requirements, supervisors and research groups.

Geographical Sciences (Physical Geography)

Find out about the University of Bristol's PhD in Geographical Sciences (Physical Geography), including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in German, including entry requirements, supervisors and research groups.

Global Challenges and Transformations

Find out about the University of Bristol's PhD in Global Challenges and Transformations, including entry requirements, supervisors and research groups.

Great Western Four+ Doctoral Training Partnership (NERC)

Find out about the Great Western Four+ Doctoral Training Partnership, a multidisciplinary training environment for postgraduate students in NERC sciences.

Health and Wellbeing

Find out about the University of Bristol's PhD in Health and Wellbeing, including entry requirements, supervisors and research groups.

Hispanic, Portuguese and Latin American Studies

Find out about the University of Bristol's PhD in Hispanic, Portuguese and Latin American Studies, including supervisors and research groups.

Find out about the University of Bristol's PhD in History, including entry requirements, supervisors and research groups.

History of Art

Find out about the University of Bristol's PhD in History of Art, including entry requirements, supervisors and research groups.

Innovation and Entrepreneurship

Find out about the University of Bristol's PhD in Innovation and Entrepreneurship, including entry requirements, supervisors and research groups.

Integrative Cardiovascular Science (BHF)

Find out about the University of Bristol's PhD in Integrative Cardiovascular Science (BHF), including entry requirements, funding and structure.

Find out about the University of Bristol's PhD in Italian, including entry requirements, structure and research groups.

Find out about the University of Bristol's PhD in Law, including entry requirements, structure and research groups.

Linguistics

Llm law - banking and finance law.

Find out about the University of Bristol's LLM in Banking and Finance Law, including structure, entry requirements and career prospects.

LLM Law - Commercial Law

Find out about the University of Bristol's LLM in Commercial Law, including structure, entry requirements and career prospects.

LLM Law - Company Law and Corporate Governance

Find out about the University of Bristol's LLM in Company Law and Corporate Governance, including structure, entry requirements and career prospects.

LLM Law - Employment, Work and Equality

Find out about the University of Bristol's LLM in Employment, Work and Equality Law, including structure, entry requirements and career prospects.

LLM Law - General Legal Studies

Find out about the University of Bristol's LLM in General Legal Studies, including structure, entry requirements and career prospects.

LLM Law - Health, Law and Society

Find out about the University of Bristol's LLM in Health, Law and Society, including structure, entry requirements and career prospects.

LLM Law - Human Rights Law

Find out about the University of Bristol's LLM in Human Rights Law, including structure, entry requirements and career prospects.

LLM Law - International Commercial Law

Find out about the University of Bristol's LLM in International Commercial Law, including structure, entry requirements and career prospects.

LLM Law - International Law

Find out about the University of Bristol's LLM in International Law, including structure, entry requirements and career prospects.

LLM Law - International Law and International Relations

Find out about the University of Bristol's LLM in International Law and International Relations, including structure, entry requirements and career prospects.

LLM Law, Environment, Sustainability & Business

Find out about the University of Bristol's LLM in Law, Environment, Sustainability and Business, including structure, entry requirements and career prospects.

LLM Law, Innovation & Technology

Find out about the University of Bristol's LLM in Law, Innovation and Technology, including structure, entry requirements and career prospects.

MA Anthropology

Find out about the University of Bristol's MA in Anthropology, including structure, entry requirements and career prospects.

MA Black Humanities

Ma chinese-english audiovisual translation.

Find out about the University of Bristol's MA in Chinese-English Audiovisual Translation, including structure, entry requirements and career prospects.

MA Chinese-English Translation

Find out about the University of Bristol's MA in Chinese-English Translation, including structure, entry requirements and career prospects.

MA Comparative Literatures and Cultures

Find out about the University of Bristol's MA in Comparative Literatures and Cultures, including structure, entry requirements and career prospects.

MA Composition of Music for Film and Television

Find out about the University of Bristol's MA in Composition of Music for Film and Television, including structure, entry requirements and career prospects.

MA Creative Innovation and Entrepreneurship

Find out about the University of Bristol's MA in Creative Innovation and Entrepreneurship, including structure, entry requirements and career prospects.

MA Creative Writing

Find out about the University of Bristol's MA in Creative Writing, including structure, entry requirements and career prospects.

MA English Literature

Find out about the University of Bristol's MA in English Literature, including structure, entry requirements and career prospects.

MA Environmental Humanities

Find out about the University of Bristol's MA in Environmental Humanities, including structure, entry requirements and career prospects.

MA Film and Television

Find out about the University of Bristol's MA in Film and Television, including structure, entry requirements and career prospects.

Find out about the University of Bristol's MA in History, including structure, entry requirements and career prospects.

MA History of Art

Find out about the University of Bristol's MA in History of Art, including structure, entry requirements and career prospects.

MA Immersive Arts (Virtual and Augmented Reality)

Find out about the University of Bristol's MSc, PGCert and PGDip in Immersive Arts (Virtual and Augmented Reality) including structure and career prospects.

Find out about the University of Bristol's MA in Law, including structure, entry requirements and career prospects.

MA Medieval Studies

Find out about the University of Bristol's MA in Medieval Studies, including structure, entry requirements and career prospects.

Find out about the University of Bristol's MA in Music, including structure, entry requirements and career prospects.

MA Philosophy

Ma translation (online).

Find out about the University of Bristol's PhD in Management, including entry requirements, structure and research groups.

Mathematics

Find out about the University of Bristol's PhD in Mathematics, including entry requirements, structure and research groups.

Mechanical Engineering

Find out about the University of Bristol's PhD in Mechanical Engineering, including entry requirements, supervisors and research groups.

Medieval Studies

Find out about the University of Bristol's PhD in Medieval Studies, including entry requirements, supervisors and research groups.

Molecular, Genetic and Lifecourse Epidemiology (Wellcome)

Find out about the University of Bristol's PhD in Molecular, Genetic and Lifecourse Epidemiology, fully funded by the Wellcome Trust for UK students.

MRes Advanced Quantitative Methods

Find out about the University of Bristol's MRes in Advanced Quantitative Methods, including structure, entry requirements and career prospects.

MRes Economics

Find out about the University of Bristol's MRes in Economics, including structure, entry requirements and career prospects.

MRes Education

Find out about the University of Bristol's MRes in Education, including structure, entry requirements and career prospects.

MRes Health Sciences Research

Find out about the University of Bristol's MRes in Health Sciences Research, including structure, entry requirements and career prospects.

MRes Sustainable Futures

Find out about the University of Bristol's MRes in Sustainable Futures, including structure, entry requirements and career prospects.

MSc Accounting and Finance

Find out about the University of Bristol's MSc in Accounting and Finance, including structure, entry requirements and career prospects.

MSc Accounting, Finance and Management

Find out about the University of Bristol's MSc in Accounting, Finance and Management, including structure, entry requirements and career prospects.

MSc Advanced Composites

Find out about the University of Bristol's MSc in Advanced Composites, including structure, entry requirements and career prospects.

MSc Advanced Microelectronic Systems Engineering

Find out about the University of Bristol's MSc in Advanced Microelectronic Systems Engineering, including structure, entry requirements and career prospects.

MSc Aerial Robotics

Find out about the University of Bristol's MSc in Aerial Robotics, including structure, entry requirements and career prospects.

MSc Applied Neuropsychology

Find out about the University of Bristol's MSc in Applied Neuropsychology, including structure, entry requirements and career prospects.

MSc Applied Neuropsychology (Online)

Msc banking, regulation and financial stability.

Find out about the University of Bristol's MSc in Banking, Regulation and Financial Stability, including structure, entry requirements and career prospects.

MSc Bioinformatics

Find out about the University of Bristol's MSc in Bioinformatics, including structure, entry requirements and career prospects.

MSc Biomedical Sciences Research

Find out about the University of Bristol's MSc in Biomedical Sciences Research, including structure, entry requirements and career prospects.

MSc Biorobotics

Find out about the University of Bristol's MSc in Biorobotics, including structure, entry requirements and career prospects.

MSc Business Analytics

Find out about the University of Bristol's MSc in Business Analytics, including structure, entry requirements and career prospects.

MSc Business Innovation and Entrepreneurship

Find out about the University of Bristol's MSc in Innovation and Entrepreneurship, including structure, entry requirements and career prospects.

MSc by research Global Environmental Challenges

Find out about the University of Bristol's MSc by research Global Environmental Challenges, including structure, entry requirements and career prospects.

MSc Cardiovascular Perfusion (Online)

Msc climate change science and policy.

Find out about the University of Bristol's MSc in Climate Change Science and Policy, including structure, entry requirements and career prospects.

MSc Clinical Neuropsychology

Find out about the University of Bristol's MSc in Clinical Neuropsychology, including structure, entry requirements and career prospects.

MSc Clinical Perfusion Science

Msc clinical research methods and evidence-based medicine, msc communication networks and signal processing.

Find out about the University of Bristol's MSc in Communication Networks and Signal Processing, including structure, entry requirements and career prospects.

MSc Computer Science (Conversion)

Find out about the University of Bristol's MSc conversion programme in Computer Science, including structure, entry requirements and career prospects.

MSc Contemporary Identities

Find out about the University of Bristol's MSc in Contemporary Identities, including structure, entry requirements and career prospects.

MSc Cyber Security (Infrastructures Security)

Find out about the University of Bristol's MSc in Cyber Security (Infrastructures Security), including structure, entry requirements and career prospects.

MSc Data Science

Find out about the University of Bristol's MSc in Data Science, including structure, entry requirements and career prospects.

MSc Data Science (Online)

Msc dental implantology.

Find out about the University of Bristol's MSc in Dental Implantology, including structure, entry requirements and career prospects.

MSc Development and Security

Find out about the University of Bristol's MSc in Development and Security, including structure, entry requirements and career prospects.

MSc Digital Health

Find out about the University of Bristol's MSc in Digital Health, including structure, entry requirements and career prospects.

MSc Earthquake Engineering and Infrastructure Resilience

Find out about the University of Bristol's MSc in Earthquake Engineering and Infrastructure Resilience, including structure and career prospects.

MSc East Asian Development and the Global Economy

Find out about the University of Bristol's MSc in East Asian Development and the Global Economy, including structure and career prospects.

MSc Economics

Find out about the University of Bristol's MSc in Economics, including structure, entry requirements and career prospects.

MSc Economics and Finance

Find out about the University of Bristol's MSc in Economics and Finance, including structure, entry requirements and career prospects.

MSc Economics with Data Science

Find out about the University of Bristol's MSc in Economics with Data Science, including structure, entry requirements and career prospects.

MSc Economics, Finance and Management

Find out about the University of Bristol's MSc in Economics, Finance and Management including structure, entry requirements and career prospects.

MSc Education (Education and Climate Change)

Find out about the University of Bristol's MSc in Education (Education and Climate Change), including structure, entry requirements and career prospects.

MSc Education (Inclusive Education)

Find out about the University of Bristol's MSc in Education (Inclusive Education), including structure, entry requirements and career prospects.

MSc Education (Leadership and Policy)

Find out about the University of Bristol's MSc in Education (Leadership and Policy), including structure, entry requirements and career prospects.

MSc Education (Learning, Technology and Society)

Find out about the University of Bristol's MSc in Education (Learning, Technology and Society), including structure, entry requirements and career prospects.

MSc Education (Mathematics Education)

Find out about the University of Bristol's MSc in Education (Mathematics Education), including structure, entry requirements and career prospects.

MSc Education (Neuroscience and Education)

Find out about the University of Bristol's MSc in Education (Neuroscience and Education), including structure, entry requirements and career prospects.

MSc Education (Open Pathway)

Find out about the University of Bristol's MSc in Education (Open Pathway), including structure, entry requirements and career prospects.

MSc Education (Policy and International Development)

Find out about the University of Bristol's MSc in Education (Policy and International Development) including structure, entry requirements and career prospects.

MSc Education (Teaching and Learning)

Msc engineering mathematics.

Find out about the University of Bristol's MSc in Engineering Mathematics, including structure, entry requirements and career prospects.

MSc Engineering with Management

Find out about the University of Bristol's MSc in Engineering with Management, including structure, entry requirements and career prospects.

MSc Environmental Analytical Chemistry

Msc environmental modelling and data analysis.

Find out about the University of Bristol's MSc in Environmental Modelling and Data Analysis, including structure, entry requirements and career prospects.

MSc Environmental Policy and Management

Find out about the University of Bristol's MSc in Environmental Policy and Management, including structure, entry requirements and career prospects.

MSc Epidemiology

Find out about the University of Bristol's MSc in Epidemiology, including structure, entry requirements and career prospects.

MSc Finance and Investment

Find out about the University of Bristol's MSc in Finance and Investment, including structure, entry requirements and career prospects.

MSc Financial Technology

Find out about the University of Bristol's MSc in Financial Technology, including structure, entry requirements and career prospects.

MSc Financial Technology with Data Science

Find out about the University of Bristol's MSc in Financial Technology with Data Science, including structure, entry requirements and career prospects.

MSc Gender and International Relations

Find out about the University of Bristol's MSc in Gender and International Relations, including structure, entry requirements and career prospects.

MSc Geographic Data Science and Spatial Analytics

Find out about the University of Bristol's MSc in Geographic Data Science and Spatial Analytics, including structure, entry requirements and career prospects.

MSc Global Development and Environment

Find out about the University of Bristol's MSc in Global Development and Environment, including structure, entry requirements and career prospects.

MSc Global Operations and Supply Chain Management

Find out about the University of Bristol's MSc in Global Operations and Supply Chain Management, including structure, entry requirements and career prospects.

MSc Global Wildlife Health and Conservation

Find out about the University of Bristol's MSc in Global Wildlife Health and Conservation, including structure, entry requirements and career prospects.

MSc Health Economics and Health Policy Analysis

Find out about the University of Bristol's MSc in Health Economics and Health Policy Analysis, including structure, entry requirements and career prospects.

MSc Health Professions Education

Msc health professions education (online), msc healthcare management (online), msc human geography: society and space.

Find out about the University of Bristol's MSc in Human Geography: Society and Space, including structure, entry requirements and career prospects.

MSc Human Resource Management and the Future of Work

Find out about the University of Bristol's MSc in Human Resource Management and the Future of Work, including structure and career prospects.

MSc Human-Computer Interaction (Online)

Msc image and video communications and signal processing.

Find out about the University of Bristol's MSc in Image and Video Communications and Signal Processing, including structure and career prospects.

MSc Immersive Technologies (Virtual and Augmented Reality)

Find out about the University of Bristol's MSc in Immersive Technologies (Virtual and Augmented Reality), including structure and career prospects.

MSc Innovation and Entrepreneurship

Msc international business and strategy: global challenges.

Find out about the University of Bristol's MSc in International Business and Strategy: Global Challenges), including structure and career prospects.

MSc International Development

Find out about the University of Bristol's MSc in International Development, including structure, entry requirements and career prospects.

MSc International Relations

Find out about the University of Bristol's MSc in International Relations, including structure, entry requirements and career prospects.

MSc International Security

Find out about the University of Bristol's MSc in International Security, including structure, entry requirements and career prospects.

MSc Management

Find out about the University of Bristol's MSc in Management, including structure, entry requirements and career prospects.

MSc Management (CSR and Sustainability)

Find out about the University of Bristol's MSc in Management (CSR and Sustainability), including structure, entry requirements and career prospects.

MSc Management (Digitalisation and Big Data)

Find out about the University of Bristol's MSc in Management (Digitalisation and Big Data), including structure, entry requirements and career prospects.

MSc Management (Entrepreneurship and Innovation)

Find out about the University of Bristol's MSc in Management (Entrepreneurship and Innovation), including structure, entry requirements and career prospects.

MSc Management (International Business)

Find out about the University of Bristol's MSc in Management (International Business), including structure, entry requirements and career prospects.

MSc Management (International Human Resource Management)

Find out about the University of Bristol's MSc in Management (International Human Resource Management), including structure and career prospects.

MSc Management (Marketing)

Find out about the University of Bristol's MSc in Management (Marketing), including structure, entry requirements and career prospects.

MSc Management (Project Management)

Find out about the University of Bristol's MSc in Management (Project Management), including structure, entry requirements and career prospects.

MSc Marketing

Find out about the University of Bristol's MSc in Marketing, including structure, entry requirements and career prospects.

MSc Mathematical Sciences

Find out about the University of Bristol's MSc in Mathematical Sciences, including structure, entry requirements and career prospects.

MSc Medical Statistics and Health Data Science

Find out about the University of Bristol's MSc in Medical Statistics and Health Data Science, including structure, entry requirements and career prospects.

MSc Molecular Neuroscience

Find out about the University of Bristol's MSc in Molecular Neuroscience, including structure, entry requirements and career prospects.

MSc Nuclear Science and Engineering

Find out about the University of Bristol's MSc in Nuclear Science and Engineering, including structure, entry requirements and career prospects.

MSc Nutrition, Physical Activity and Public Health

Find out about the University of Bristol's MSc in Nutrition, Physical Activity and Public Health, including structure, entry requirements and career prospects.

MSc Optical Communications and Signal Processing

Find out about the University of Bristol's MSc in Optical Communications and Signal Processing, including structure, entry requirements and career prospects.

MSc Optoelectronic and Quantum Technologies

Find out about the University of Bristol's MSc in Optoelectronic and Quantum Technologies, including structure, entry requirements and career prospects.

MSc Oral Medicine

Find out about the University of Bristol's MSc in Oral Medicine, including structure, entry requirements and career prospects.

MSc Palaeobiology

Find out about the University of Bristol's MSc in Palaeobiology, including structure, entry requirements and career prospects.

MSc Periodontology

Find out about the University of Bristol's MSc and Postgraduate Certificate in Perfusion Science, including structure, entry requirements and career prospects.

MSc Policy Research

Find out about the University of Bristol's MSc in Policy Research, including structure, entry requirements and career prospects.

MSc Psychology (Conversion)

Msc psychology of education bps.

Find out about the University of Bristol's MSc conversion programme in Psychology of Education, accreddiated by the British Psychological Society,

MSc Public Health

Find out about the University of Bristol's MSc in Public Health, including structure, entry requirements and career prospects.

MSc Public Policy

Find out about the University of Bristol's MSc in Public Policy, including structure, entry requirements and career prospects.

MSc Reproduction and Development

Find out about the University of Bristol's MSc, PGCert and PGDip in Reproduction and Development, including structure, entry requirements and career prospects.

MSc Robotics

Find out about the University of Bristol's MSc in Robotics, including structure, entry requirements and career prospects.

MSc Science Communication for a Better Planet

Find out about the University of Bristol's MSc in Science Communication for a Better Planet, including structure, entry requirements and career prospects.

MSc Scientific Computing with Data Science

Find out about the University of Bristol's MSc in Scientific Computing with Data Science, including structure, entry requirements and career prospects.

MSc Social and Cultural Theory

Find out about the University of Bristol's MSc in Social and Cultural Theory, including structure, entry requirements and career prospects.

MSc Social Innovation and Entrepreneurship

Find out about the University of Bristol's MSc in Social Innovation and Entrepreneurship, including structure, entry requirements and career prospects.

MSc Social Science Research Methods (Management)

Find out about the University of Bristol's MSc in Social Science Research Methods (Management), including structure, entry requirements and career prospects.

MSc Social Science Research Methods (Politics)

Find out about the University of Bristol's MSc in Social Science Research Methods (Politics), including structure, entry requirements and career prospects.

MSc Social Science Research Methods (Sociology)

Find out about the University of Bristol's MSc in Social Science Research Methods (Sociology), including structure, entry requirements and career prospects.

MSc Social Work

Find out about the University of Bristol's MSc in Social Work, including structure, entry requirements and career prospects.

MSc Social Work Research

Find out about the University of Bristol's MSc in Social Work Research, including structure, entry requirements and career prospects.

MSc Society, Politics and Climate Change

Find out about the University of Bristol's MSc in Society, Politics and Climate Change, including structure, entry requirements and career prospects.

MSc Socio-Legal Studies

Find out about the University of Bristol's MSc in Socio-Legal Studies, including structure, entry requirements and career prospects.

MSc Sociology

Find out about the University of Bristol's MSc in Sociology, including structure, entry requirements and career prospects.

MSc Stem Cells and Regeneration (Online)

Msc strategy, change and leadership.

Find out about the University of Bristol's MSc and PGCert in Strategy, Change and Leadership, including structure, entry requirements and career prospects.

MSc Sustainable Engineering

Msc teaching english to speakers of other languages (tesol).

Find out about the University of Bristol's MSc in Teaching English to Speakers of Other Languages, including structure, entry requirements and career prospects.

MSc Technology Innovation and Entrepreneurship

Find out about the University of Bristol's MSc in Technology Innovation and Entrepreneurship, including structure, entry requirements and career prospects.

MSc Translational Cardiovascular Medicine

Find out about the University of Bristol's MSc, PGCert and PGDip in Translational Cardiovascular Medicine, including structure and entry requirements.

MSc Translational Cardiovascular Medicine (Online)

Msc water and environmental management.

Find out about the University of Bristol's MSc in Water and Environmental Management, including structure, entry requirements and career prospects.

MSc Wireless Communications and Signal Processing

Find out about the University of Bristol's MSc in Wireless Communications and Signal Processing, including structure, entry requirements and career prospects.

Find out about the University of Bristol's PhD in Music, including entry requirements, supervisors and research groups.

Oral and Dental Sciences

Find out about the University of Bristol's PhD in Oral and Dental Sciences, including entry requirements, supervisors and research groups.

PG Certificate (Postgraduate Certificate) Clinical Neuropsychology Practice

Find out about the University of Bristol's Postgraduate Certificate in Clinical Neuropsychology Practice, including structure and career prospects.

PG Certificate (Postgraduate Certificate) Clinical Oral Surgery

Find out about the University of Bristol's Postgraduate Certificate in Clinical Oral Surgery, including structure, entry requirements and career prospects.

PG Certificate (Postgraduate Certificate) Clinical Perfusion Science

Pg certificate (postgraduate certificate) healthcare improvement (online), pg diploma (postgraduate diploma) applied neuropsychology, pg diploma (postgraduate diploma) applied neuropsychology (online), pg diploma (postgraduate diploma) clinical neuropsychology.

Find out about the University of Bristol's Postgraduate Diploma in Clinical Neuropsychology, including structure, entry requirements and career prospects.

PG Diploma (Postgraduate Diploma) Orthodontic Therapy

Pg diploma (postgraduate diploma) theoretical and practical clinical neuropsychology.

Find out about the University of Bristol's PG Diploma in Theoretical and Practical Clinical Neuropsychology, including structure and entry requirements.

PGCE Education (Secondary)

Find out about the University of Bristol's PGCE in Education (Secondary) including structure, entry requirements and career prospects.

Find out about the University of Bristol's PhD in Philosophy, including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in Physics, including entry requirements, supervisors and research groups.

Physiology, Pharmacology and Neuroscience

Find out about the University of Bristol's PhD in Physiology, Pharmacology and Neuroscience, including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in Politics, including key themes and entry requirements.

Population Health Sciences

Find out about the University of Bristol's PhD in Population Health Sciences, including entry requirements, career prospects and research groups.

Practice-Oriented Artificial Intelligence

Quantum information science and technologies, religion and theology.

Find out about the University of Bristol's PhD in Religion and Theology, including structure, entry requirements and supervisors.

Find out about the University of Bristol's PhD in Russian, including entry requirements, supervisors and research groups.

Social Policy

Find out about the University of Bristol's PhD in Social Policy, including entry requirements, supervisors and research groups.

Social Work

Find out about the University of Bristol's PhD in Social Work, including entry requirements, supervisors and research groups.

Find out about the University of Bristol's PhD in Sociology, including entry requirements, supervisors and research groups.

Sociotechnical Futures and Digital Methods

Find out about the University of Bristol's PhD in Sociotechnical Futures and Digital Methods, including entry requirements, supervisors and research groups.

South West Biosciences Doctoral Training Partnership (BBSRC)

Find out about the University of Bristol's South West Biosciences Doctoral Training Partnership, including structure and entry requirements.

Sustainable Futures

Find out about the University of Bristol's PhD in Sustainable Futures, including entry requirements, supervisors and research groups.

Technology Enhanced Chemical Synthesis

Find out about the University of Bristol's PhD in Technology Enhanced Chemical Synthesis, including entry requirements, supervisors and research groups.

Theatre and Performance

Find out about the University of Bristol's PhD in Theatre and Performance, including entry requirements, supervisors and research groups.

Translation

Find out about the University of Bristol's PhD in Translation, including entry requirements, supervisors and research groups.

Translational Health Sciences

Find out about the University of Bristol's PhD in Translational Health Sciences, including entry requirements, supervisors and research groups.

Veterinary Sciences

Find out about the University of Bristol's PhD in Veterinary Sciences, including entry requirements, research groups and career prospects.

Machine Learning (Ph.D.)

The curriculum for the PhD in Machine Learning is truly multidisciplinary, containing courses taught in eight schools across three colleges at Georgia Tech: the Schools of Computational Science and Engineering, Computer Science, and Interactive Computing in the College of Computing; the Schools of Industrial and Systems Engineering, Electrical and Computer Engineering, and Biomedical Engineering in the College of Engineering; and the School of Mathematics in the College of Science.

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PhD in Technology – Artificial Intelligence and Machine Learning Specialization

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Immerse yourself in cutting-edge research and practical applications with a PhD in Technology with a specialization in Artificial Intelligence and Machine Learning from Walsh College.

Savvy business leaders know that Artificial Intelligence (AI) and Machine Learning are the latest innovations that will change everything about the way we do business. The field is full of tools that are springing up seemingly overnight. The world as we know it is undergoing fundamental shifts. Is it possible to ride this latest wave of innovation without being knocked over by it?

With a PhD in Technology with a specialization in Artificial Intelligence and Machine Learning from Walsh College, you will be positioned as a visionary trailblazer in this vitally important field. Tailored for working professionals, the program integrates online coursework and Zoom-enabled remote delivery, allowing seamless navigation of advanced studies alongside professional commitments.

In the PhD in Technology with a specialization in Artificial Intelligence and Machine Learning program, you will embark on a journey that delves into the core of artificial intelligence and machine learning, from advanced research in natural language processing to the practical applications of deep learning theory. As a PhD graduate in AI and Machine Learning, you will be at the forefront of technological innovation, equipped to lead in an era defined by data, algorithms, and intelligent systems.

Faculty With Real-World Experience

There’s no substitute for experience. 95% of Walsh faculty bring their real-world industry experience into the classroom . You will learn from proven business minds who have worked or are working in the roles you may see yourself in one day.

Flexible Learning Options

Recognizing the diverse needs of our students, Walsh College offers a range of flexible learning options. Whether you prefer traditional on-campus classes, online learning, or a hybrid approach, we have a solution that fits your lifestyle.

Career Services & Networking Events

Your success extends beyond the classroom, and we are committed to supporting your career aspirations. Walsh provides comprehensive career services, including resume workshops, networking events, and job placement assistance to help you launch your professional journey.

Streamlined Dissertation Process

Our dissertation process is designed to provide candidates with support from start to finish. Faculty responsiveness, clear expectations, established milestones, and adequate mentoring all play a vital role in helping successfully guide students through their dissertations.

A Network of Support

Our knowledgeable, professional staff will be there to help from your first contact to the day you graduate. With free tutoring, professional mentoring, and networking opportunities throughout the year, you’ll have the resources you need for academic and professional success.

Overview, Courses, and Graduation Requirements

Phd in technology – artificial intelligence and machine learning, admission requirements, doctoral degree admission requirements, walsh making a difference..

There are a lot of reasons students love attending Walsh. Listen to some of our alumni share what made Walsh the right fit for them.

FastTrack Your Education

FastTrack  is an accelerated degree program that lets you earn credits for both a master’s and doctoral degree at the same time. Meet with a Walsh Enrollment Specialist to learn more.

DEGREE PLANNER

So many possibilities are unleashed when you enroll in the right Walsh program.

We want to help you find the degree that’s right for you.

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APPLY TODAY

Take the first step toward the rest of your life. Apply online or speak with an Enrollment Specialist today.

Call 248-823-1600  or email  [email protected] .

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Your Steps to A Better Future

1. Apply to Walsh

Applying is easy through our online portal. Have a few questions first? Our Enrollment Specialists are ready to help!

2. Choose Your Path

Choose online, remote synchronous, or on-ground classes at the pace that fits your goals. We’ll provide the training and skills you need to start your career and/or head into your certification exam with confidence.

3. Reach New Heights

With a Walsh degree on your resume and your certification in hand, you’ll be ready to advance your career and influence your company for decades.

How to Choose a Doctoral Program That’s Right for You

Transform Your Doctoral Aspirations Into RealityApply Now!Take the first step toward the rest of your life. Apply online or speak with an Enrollment Specialist today. Schedule an Appointment How to Choose a Doctoral Program That’s Right for You There are many reasons a person may choose to earn a doctorate…

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Doctor of Philosophy (PhD) in Machine Learning

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Earn a Ph.D. in Machine Learning and discover the elements of artificial intelligence, computer engineering, and data analytics involved in this evolving field.

The doctoral degree in Machine Learning explores the ways in which algorithmic data is generated and leveraged for statistical applications and computational analysis in model-based decision-making. Students will learn the current operations, international relationships, and areas of improvement in this field, as well as research methodologies and future demands of the industry.

The PhD in Machine Learning is for current or experienced professionals in a field related to machine learning, artificial intelligence, computer science, or data analytics. Students will pursue a deep proficiency in this area using interdisciplinary methodologies, cutting-edge courses, and dynamic faculty. Graduates will contribute significantly to the Machine Learning field through the creation of new knowledge and ideas, and will quickly develop the skills to engage in leadership, research, and publishing. 

As your PhD progresses, you will move through a series of progression points and review stages by your academic supervisor. This ensures that you are engaged in research that will lead to the production of a high-quality thesis and/or publications, and that you are on track to complete this in the time available. Following submission of your PhD Thesis or accepted three academic journal articles, you will have an oral presentation assessed by an external expert in your field.

Why Capitol?

Expert guidance in doctoral research

Capitol’s doctoral programs are supervised by faculty with extensive experience in chairing doctoral dissertations and mentoring students as they launch their academic careers. You’ll receive the guidance you need to successfully complete your doctoral research project and build credentials in the field.

Proven academic excellence

Study at a university that specializes in industry-focused education in technology-based fields, nationally recognized for academic excellence in our programs.

Program is 100% online

Our PhD in Machine Learning is offered 100% online, with no on-campus classes or residencies required, allowing you the flexibility needed to balance your studies and career.

Key Faculty

Vice President

Associate Chair, Director of Engineering Labs

Dissertation Chair

Career Opportunities

Market demand for machine learning expertise

Graduates will contribute significantly to the rapidly growing machine learning field through the creation of new knowledge and ideas, and will be prepared for in-demand roles such as a trusted subject matter expert, researcher, technician, manager, or professor.

This program may be completed with a minimum of 60 credit hours, but may require additional credit hours, depending on the time required to complete the dissertation/publication research. Students who are not prepared to defend after completion of the 60 credits will be required to enroll in RSC-899, a one-credit, eight-week continuation course. Students are required to be continuously enrolled/registered in the RSC-899 course until they successfully complete their dissertation defense/exegesis.

The student will produce, present, and defend a doctoral dissertation after receiving the required approvals from the student’s Committee and the PhD Review Boards.

Doctor of Philosophy in Machine Learning Courses Total Credits: 60

MACHINE LEARNING DOCTORAL CORE: 30 CREDITS

OFFENSIVE MACHINE LEARNING DOCTORAL RESEARCH AND WRITING: 30 CREDITS 

Educational Objectives:  

Students will... 

1. Integrate and synthesize alternate, divergent, or contradictory perspectives within the field of Machine Learning. 2. Demonstrate advanced knowledge and competencies in ethics of Machine Learning. 3. Analyze theories, tools, and frameworks used in Machine Learning. 4. Evaluate the legal, social, economic, environmental, and ethical impact of actions within Machine Learning. 5. Implement Machine Learning plans needed for advanced global applications.

Learning Outcomes:  

Upon graduation... 

1. Graduates will integrate the theoretical basis and practical applications of Machine Learning into their professional work.  2. Graduates will demonstrate the highest mastery of the subject matter. 3. Graduates will evaluate complex problems, synthesize divergent/alternative/contradictory perspectives and ideas fully, and develop advanced solutions to Machine Learning challenges. 4. Graduates will contribute to the body of knowledge in the study of the subject. 5. Graduates will be at the forefront of Machine Learning planning and implementation.

Tuition & Fees

Tuition rates are subject to change.

The following rates are in effect for the 2024-2025 academic year, beginning in Fall 2024 and continuing through Summer 2025:

• The application fee is $100
• The per-credit charge for doctorate courses is $950. This is the same for in-state and out-of-state students.
• Retired military receive a $50 per credit hour tuition discount
• Active duty military receive a $100 per credit hour tuition discount for doctorate level coursework.
• Information technology fee $40 per credit hour.
• High School and Community College full-time faculty and full-time staff receive a 20% discount on tuition for doctoral programs.

Find additional information for 2024-2025 doctorate tuition and fees.

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MastersInAI.org

PhD in Artificial Intelligence Programs

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Universities offer a variety of Doctor of Philosophy (Ph.D.) programs related to Artificial Intelligence (AI.) Some of these are titled as Ph.D.s in AI, whereas most are Ph.D.s in Computer Science or related engineering disciplines with a specialization or focus in AI. Admissions requirements usually include a related bachelor’s degree and, sometimes, a master’s degree. Moreover, most Ph.D. programs expect academic excellence and strong recommendations. The AI Ph.D. programs take three to five or more years, depending on if you have a master’s and the complexity of your dissertation. People with Ph.D.s in AI usually go on to tenure track professorships, postdoctoral research positions, or high-level software engineering positions.

What Are Artificial Intelligence Ph.D. Programs?

Ph.D. programs in AI focus on mastering advanced theoretical subjects, such as decision theory, algorithms, optimization, and stochastic processes. Artificial intelligence covers anything where a computer behaves, rationalizes, or learns like a human. Ph.D.s are usually the endpoint to a long educational career. By the time scholars earn Ph.D.s, they have probably been in school for well over 20 years.

People with an AI Ph.D. degree are capable of formulating and executing novel research into the subtopics of AI. Some of the subtopics include:

• Environment adaptation in self-driving vehicles
• Natural language processing in robotics
• Cheating detection in higher education
• Diagnosing and treating diseased in healthcare

AI Ph.D. programs require candidates to focus most of their coursework and research on AI topics. Most culminate in a dissertation of published research. Many AI Ph.D. recipients’ dissertations are published in peer-reviewed journals or presented at industry-leading conferences. They go on to lead careers as experts in AI technology.

Types of Artificial Intelligence Ph.D. Programs

Most AI Ph.D. programs are a Ph.D. in Computer Science with a concentration in AI. These degrees involve general, advanced level computer science courses for the first year or two and then specialize in AI courses and research for the remainder of the curriculum.

AI Ph.D.s offered in other colleges like Computer Engineering, Systems Engineering, Mechanical Engineering, or Electrical Engineering are similar to Ph.D.s in Computer Science. They often involve similar coursework and research. For instance, colleges like Indiana University Bloomington’s Computing and Engineering have departments specializing in AI or Intelligent Engineering. Some colleges, however, may focus more on a specific discipline. For example, a Ph.D. in Mechanical Engineering with an AI focus is more likely to involve electric vehicles than targeted online advertising.

Some AI programs fall under a Computational Linguistics specialization, like CUNY . These programs emphasize the natural language processing aspect of AI. Computational Linguistics programs still involve significant computer science and engineering but also require advanced knowledge in language and speech.

Other unique programs offer a joint Ph.D. with non-engineering disciplines, such as Carnegie Mellon’s Joint Ph.D. in Machine Learning and Public Policy, Statistics, or Neural Computation .

How Ph.D. in Artificial Intelligence Programs Work

Ph.D. programs usually take three to six years to complete. For example, Harvard lays out a three+ year track where the last year(s) is spent completing your research and defending your dissertation. Many Ph.D. programs have a residency requirement where you must take classes on-campus for one to three years. Moreover, most universities, such as Brandeis , require Ph.D. students to grade and/or teach for one to four semesters. Despite these requirements, several Ph.D. programs allow for part-time or full-time students, like Drexel .

Admissions Requirements

Ph.D. programs in AI admit the strongest students. Most applications require a resume, transcripts, letters of recommendation, and a statement of interest. Many programs require a minimum undergraduate GPA of 3.0 or higher, although some allow for statements of explanation if you have a lower GPA due to illness or other excusable causes for a low GPA.

Many universities, like Cornell , recently made the GRE either optional or not required because the GRE provides little prediction into the success of research and represents a COVID-19 risk. These programs may require the GRE again in the future. However, many schools still require the IELTS/TOEFL for international applicants.

Curriculum and Coursework

The curriculum for AI Ph.D.s varies based on the applicants’ prior education for many universities. Some programs allow applicants to receive credit for relevant master’s programs completed prior to admission. The programs require about 30 hours of advanced research and classes. Other programs do not give credit for master’s programs completed elsewhere. These require over 60 hours of electives, in addition to the 30-hours of fundamental and core classes in addition to the advanced courses.

For programs with more specific specialties, the courses are usually narrowly focused. For example, Duke’s Dynamics, Robotics, and Controls track requires ten classes, at least three of which are focused on AI as it relates to robotics. Others allow for non-AI-specific courses such as computer networks.

Many Ph.D. programs have strict GPA requirements to remain in the program. For example, Northeastern requires PhD candidates to maintain at least a 3.5 GPA. Other programs automatically dismiss students with too many Cs in courses.

Common specializations include:

• Computational Linguistics
• Automotive Systems
• Data Science

Artificial Intelligence Dissertations

Most Ph.D. programs require a dissertation. The dissertation takes at least two years to research and write, usually starting in the second or third year of the Ph.D. curriculum. Moreover, many programs require an oral presentation or defense of the dissertation. Some universities give an award for the best dissertation of the year. For example, Boston University gave a best dissertation award to Hao Chen for the dissertation entitled “ Improving Data Center Efficiency Through Smart Grid Integration and Intelligent Analytics .”

A couple of programs require publications, like Capitol Technology , or additional course electives, like LIU . For example, The Ohio State University requires 27 hours of graded coursework and three hours with an advisor for non-thesis path candidates. Thesis-path candidates only have to take 18 hours of graded coursework but must spend 12 hours with their advisors.

Are There Online Ph.D. in Artificial Intelligence Programs?

Officially, the majority of AI Ph.D. programs are in-person. Only one university, Capitol Technology University , allows for a fully online program. This is one of the most expensive Ph.D.s in the field, costing about $60,000. However, it is also one of the most flexible programs. It allows you to complete your coursework on your own schedule, perhaps even while working. Moreover, it allows for either a dissertation path or a publication path. The coursework is fully focused on AI research and writing, thus eliminating requirements for more general courses like algorithms or networks.

One detail you should consider is that the Capitol Technology Ph.D. program is heavily driven by a faculty mentor. This is someone you will need consistent contact with and open communication. The website only lists the director, so there is a significant element of uncertainty on how the program will work for you. But doctoral candidates who are self-driven and have a solid idea of their research path have a higher likelihood of succeeding.

If you need flexibility in your Ph.D. program, you may find some professors at traditional universities will work with you on how you meet and conduct the research, or you may find an alternative degree program that is online. Although a Ph.D. program may not be officially online, you may be able to spend just a semester or two on campus and then perform the rest of the Ph.D. requirements remotely. This is most likely possible if the university has an online master’s program where you can take classes. For example, the Georgia Institute of Technology does not have a residency requirement, has an online master’s of computer science program , and some professors will work flexibly with doctoral candidates with whom they have a close relationship.

What Jobs Can You Get with a Ph.D. in Artificial Intelligence?

Many Ph.D. graduates work as tenure track professors at universities with AI classes. Others work as postdoc research scientists at universities. Both of these roles are expected to conduct research and publish, but professors have more of an expectation to teach, as well. Universities usually have a small number of these positions available. Moreover, postdoc research positions tend to only last for a limited amount of time.

Other engineers with AI-focused-Ph.D.s conduct research and do software development in the private sector at AI-intensive companies. For example, Google uses AI in many departments. Its assistant uses natural language processing to interface with users through voice. Moreover, Google uses AI to generate news feeds for users. Google, and other industry leaders, have a strong preference for engineers with Ph.D.s. This career path is often highly sought by new Ph.D. recipients.

Another private sector industry shifting to AI is vehicle manufacturing. For example, self-driving cars use significant AI to make ethical and legal decisions while operating. Another example is that electric vehicles use AI techniques to optimize performance and power usage.

Some AI Ph.D. recipients become c-suite executives, such as Chief Technology Officers (CTO). For example, Dr. Ted Gaubert has a Ph.D. in engineering and works as a CTO for an AI-intensive company. Another CTO, Dr. David Talby , revolutionized AI with a new natural language processing library, Spark. CTO positions in AI-focused companies often have decades of experience in the AI field.

How Much Do Ph.D. in Artificial Intelligence Programs Cost?

The tuition for many Ph.D. programs is paid through fellowships, graduate research assistantships, and teaching assistantships. For example, Harvard provides full support for Ph.D. candidates. Some programs mandate teaching or research to attend based on the assumption that Ph.D. candidates need financial assistance.

Fellowships are often reserved for applicants with an exceptional academic and research background. These are usually named for eminent alumni, professors, or other scholars associated with the university. Receiving such a fellowship is a highly respected honor.

For programs that do not provide full assistance, the usual cost is about $500 to $1,000 per credit hour, plus university fees. On the low end, Northern Illinois University charges about $557 per credit hour . With 30 to 60 hours required, this means the programs cost about $30,000 to over $60,000 out of pocket. Typically, Ph.D. programs that do not provide funding for any Ph.D. candidates are less reputable or provide other benefits, such as flexibility, online programs, or fewer requirements.

How Much Does a Ph.D. in AI Make?

Engineers with AI Ph.D.s earn well into the six-figure range in the private sector. For example, OpenAI , a non-profit, pays its top researchers over $400,000 per year. Amazon pays its data scientists with Ph.D.s over $200,000 in salary. Directors and executives with Ph.D.s often earn over $1,000,000 in private industry.

When considering working in the private industry, professionals usually compare offers based on total compensation, not just salary. Many companies offer large stock and bonus packages to Ph.D.-level engineers and scientists.

Startups sometimes pay less in salary, but much more in stock options. For example, the salary may be $50,000 to $100,000, but when the startup goes public, you may end up with hundreds of thousands in stock options. This creates a sense of ownership and investment in the success of the startup.

Computer science professors and postdoctoral researchers earn about $90,000 to $160,000 from universities. However, they increase their competition by writing books, speaking at conferences, and advising companies. Startups often employ professors for advice on the feasibility and design of their technology.

Schools with PhD in Artificial Intelligence Programs

Arizona state university.

School of Computing and Augmented Intelligence

Tempe, Arizona

Ph.D. in Computer Science (Artificial Intelligence Research)

Ph.d. in computing and information sciences (artificial intelligence research), university of california-riverside.

Department of Electrical and Computer Engineering

Riverside, California

Ph.D. in Electrical Engineering - Intelligent Systems Research Area

University of california-san diego.

Electrical and Computer Engineering Department

La Jolla, California

Ph.D. in Intelligent Systems, Robotics and Control

Colorado state university-fort collins.

The Graduate School

Fort Collins, Colorado

Ph.D. in Computer Science - Artificial Intelligence Research Area

University of colorado boulder.

Paul M. Rady Mechanical Engineering

Boulder, Colorado

PhD in Robotics and Systems Design

District of columbia, georgetown university.

Department of Linguistics

Washington, District of Columbia

Doctor of Philosophy (Ph.D.) in Linguistics - Computational Linguistics

The university of west florida.

Department of Intelligent Systems and Robotics

Pensacola, Florida

Ph.D. in Intelligent Systems and Robotics

University of central florida.

Department of Electrical & Computer Engineering

Orlando, Florida

Doctorate in Computer Engineering - Intelligent Systems and Machine Learning

Georgia institute of technology.

Colleges of Computing, Engineering, and Sciences

Atlanta, Georgia

Ph.D. in Machine Learning

Northern illinois university.

Dekalb, Illinois

Ph.D. in Computer Science - Artificial Intelligence Area of Emphasis

Ph.d. in computer science - machine learning area of emphasis, northwestern university.

McCormick School of Engineering

Evanston, Illinois

PhD in Computer Science - Artificial Intelligence and Machine Learning Research Group

Indiana university bloomington.

Department of Intelligent Systems Engineering

Bloomington, Indiana

Ph.D. in Intelligent Systems Engineering

Ph.d. in linguistics - computational linguistics concentration, capitol technology university.

Doctoral Programs Department

Laurel, Maryland

Doctor of Philosophy (PhD) in Artificial Intelligence

Offered Online

Johns Hopkins University

Whiting School of Engineering

Baltimore, Maryland

Doctor of Philosophy in Mechanical Engineering - Robotics

Massachusetts, boston university.

College of Engineering

Boston, Massachusetts

PhD in Computer Engineering - Data Science and Intelligent Systems Research Area

Phd in systems engineering - automation, robotics, and control, brandeis university.

Department of Computer Science

Waltham, Massachusetts

Ph.D. in Computer Science - Computational Linguistics

Harvard university.

School of Engineering and Applied Sciences

Cambridge, Massachusetts

Ph.D. in Applied Mathematics

Northeastern university.

Khoury College of Computer Science

Ph.D. in Computer Science - Artificial Intelligence Area

University of michigan-ann arbor.

Electrical Engineering and Computer Science Department

Ann Arbor, Michigan

PhD in Electrical and Computer Engineering - Robotics

University of nebraska at omaha.

College of Information Science & Technology

Omaha, Nebraska

PhD in Information Technology - Artificial Intelligence Concentration

University of nevada-reno.

Computer Science and Engineering Department

Reno, Nevada

Ph.D. in Computer Science & Engineering - Intelligent and Autonomous Systems Research

Rutgers university.

New Brunswick, New Jersey

Ph.D. in Linguistics with Computational Linguistics Certificate

Stevens institute of technology.

Schaefer School Of Engineering & Science

Hoboken, New Jersey

Ph.D. in Computer Engineering

Ph.d. in electrical engineering - applied artificial intelligence, ph.d. in electrical engineering - robotics and smart systems research, cornell university.

Ithaca, New York

Linguistics Ph.D. - Computational Linguistics

Ph.d.in computer science, cuny graduate school and university center.

New York, New York

Ph.D. in Linguistics - Computational Linguistics

Long island university-brooklyn campus.

Graduate Department

Brooklyn, New York

Dual PharmD/M.S. in Artificial Intelligence

Rochester institute of technology.

Golisano College of Computing and Information Sciences

Rochester, New York

North Carolina

Duke university.

Duke Robotics

Durham, North Carolina

Ph.D in ECE - Robotics Track

Ph.d. in mems - robotics track, ohio state university-main campus.

Department of Mechanical and Aerospace Engineering

Columbus, Ohio

PhD in Mechanical Engineering - Automotive Systems and Mobility (Connected and Automated Vehicles)

University of cincinnati.

College of Engineering and Applied Science

Cincinnati, Ohio

PhD in Computer Science and Engineering - Intelligent Systems Group

Oregon state university.

Corvallis, Oregon

Ph.D. in Artificial Intelligence

Pennsylvania, carnegie mellon university.

Machine Learning Department

Pittsburgh, Pennsylvania

PhD in Machine Learning & Public Policy

Phd in neural computation & machine learning, phd in statistics & machine learning, phd program in machine learning, drexel university.

Philadelphia, Pennsylvania

Doctorate in Mechanical Engineering - Robotics and Autonomy

Temple university.

Computer & Information Sciences Department

PhD in Computer and Information Science - Artificial Intelligence

University of pittsburgh-pittsburgh campus.

School of Computing and Information

Ph.D. in Intelligent Systems

The university of texas at austin.

Austin, Texas

Ph.D. with Graduate Portfolio Program in Robotics

The university of texas at dallas.

Erik Jonsson School of Engineering and Computer Science

Richardson, Texas

University of Utah

Mechanical Engineering Department

Salt Lake City, Utah

Doctor of Philosophy - Robotics Track

University of washington-seattle campus.

Seattle, Washington

Ph.D. in Machine Learning and Big Data

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PhD in Human-Inspired Artificial Intelligence

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This exciting PhD in Human-Inspired Artificial Intelligence will train the next generation of AI researchers, technologists, and leaders in the development of human-centred, human-compatible, responsible and socially and globally beneficial AI technologies. The course offers research training in areas such as fundamental human-level AI, social and interactive AI, cognitive AI, creative AI, health and global AI, and responsible AI. Students will be educated in an interdisciplinary environment where they can get access to expertise not only in the technical but also human, ethical, applied and industrial aspects of AI.

This programme is distinct from other PhD programmes in that it takes a strongly interdisciplinary and cross-disciplinary approach to technical AI. It will be based at the Centre for Human-Inspired Artificial Intelligence (CHIA) within the Institute for Technology and Humanity (ITH) where PhD students will have access to both a large community of scholars and students tackling similar questions and to the active research events programme that constitutes a key part of CHIA’s work. The course addresses the broader need for experts equipped to develop more responsible and human-centred AI as academia, industry, government and non-profit sectors increasingly recruit AI specialists and is a logical next step for students moving through AI-related master’s programmes and wishing to specialise in human-inspired AI. The interdisciplinary nature of human-inspired AI means that the programme will involve working closely also with other units of the University, including co-supervision arrangements, access to research seminars, and access to facilities.

The PhD in Human-Inspired AI aims to equip students with the skills and knowledge to contribute critically and constructively to research in human-inspired AI. It introduces students from diverse backgrounds to research skills and specialist knowledge from a range of academic disciplines and provides them with the opportunity to carry out focused research under close supervision by domain experts at the University.

The programme will train the next generation of researchers and leaders in AI by

• providing them with educational infrastructure and interdisciplinary research environment and world-leading training in human-inspired AI,
• providing them with the critical tools to engage with the forefront of academic knowledge, methods and applications in this area,
• developing the advanced skills and abilities to identify, approach and address practical interdisciplinary research challenges,
• supporting students to develop a broad and deep understanding of the technical, ethical, applied and human aspects of AI, 
• developing the ability and initiative to identify, address and approach relevant and complex challenges across sectors and society.

The course will benefit  

• students wanting to engage with human-inspired AI by enabling them to hone critical, methodological and technical skills, develop new approaches and test them out, and specialise,
• students locating themselves in other home disciplines who wish to develop advanced projects including CHIAs approaches and orientations, 
• students entering into or returning to careers in academia, tech industry, and other sectors by giving them the advanced skills, critical perspectives, and methodological insights to pursue these pathways.

Learning Outcomes

Knowledge and Understanding

By the end of the PhD programme our graduates will demonstrate:

• The ability to create and interpret new knowledge, through original research or other advanced scholarship of a quality to satisfy peer review, extend the forefront of the discipline, and merit publication.
• The general ability to conceptualise, design and implement a project for the generation of new knowledge, applications or understanding at the forefront of human-inspired AI, and to adjust the project design in the light of unforeseen problems.
• A detailed understanding of applicable techniques for cross-disciplinary research and advanced academic enquiry in the field of human-inspired AI
• The ability to make informed judgements on complex issues in human inspired AI, often in the absence of complete data.
• A critical perspective on the governance and ethical challenges that arise from applications of human-inspired AI and how these sit within and interact with wider society. 
• A systematic acquisition and understanding of a substantial body of knowledge in relation to the history, methods, and applications of human-inspired AI.

Skills and other attributes

Graduates of the course will be able to:

• Continue to undertake pure and/or applied research and development at an advanced level, contributing substantially to the development of new techniques, ideas or approaches.
• Communicate their ideas and conclusions clearly and effectively to specialist and non-specialist audiences.
• Contribute constructively within national, international and cross-disciplinary environments.
• Transfer skills and qualities acquired during the programme to successfully engage in employment requiring the exercise of personal responsibility and largely autonomous initiative in complex and unpredictable situations, in professional or equivalent environments.

Employability

Students of the programme will graduate with a formal qualification in the rapidly expanding area of AI. The emphasis is on human-inspired AI. The combination of specialist, technical expertise in AI and cross-disciplinary approaches involving a wide range of human-centric disciplines means that our doctoral graduates will be uniquely qualified in the sector. The PhD will, therefore, put them in a strong position to pursue careers in a variety of academic and non-academic settings, for example organisations and consultancies in diverse sectors such as tech, health, environment, education, journalism, civil service among others.

For those intending to continue into an academic career, the course will equip them with the skills, experience and qualification for applying for a postdoctoral research position.

For Cambridge students applying to continue from the MPhil to a PhD, students must achieve a pass in the MPhil by Thesis or an overall distinction in the MPhil by Advanced Study.

All applications are judged on their own merits, and students must demonstrate their suitability to undertake doctoral-level research.

The Centre for Human-Inspired Artificial Intelligence (CHIA) will hold an online webinar 9:00-9:45am on 4 November 2024.  Please see the  CHIA website  for information on how to register for this event. 

The Cambridge University Postgraduate Virtual Open Day usually takes place at the beginning of November.  It's a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

See further the  Postgraduate Admissions Events  pages for other events relating to Postgraduate study, including study fairs, visits and international events.

Key Information

3-4 years full-time, 4-7 years part-time, study mode : research, doctor of philosophy, institute for technology and humanity, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, michaelmas 2025.

Some courses can close early. See the Deadlines page for guidance on when to apply.

Funding Deadlines

These deadlines apply to applications for courses starting in Michaelmas 2025, Lent 2026 and Easter 2026.

Similar Courses

• Human-Inspired Artificial Intelligence MPhil
• Global Risk and Resilience MPhil
• Future Infrastructure and Built Environment EPSRC CDT PhD
• Conservation Leadership MPhil
• Chemistry MPhil

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PhD in Health Artificial Intelligence

Artificial Intelligence (AI) is permeating every aspect of research and healthcare. Our PhD in Health AI at  Cedars-Sinai  equips students with cutting-edge AI approaches, emphasizing the optimal use of clinical data to inform patient care. Through active learning, clinical rotations and collaboration with clinicians, our program ensures graduates are poised to navigate and contribute to the dynamic world of AI in medical research and patient well-being.

Cedars-Sinai 's PhD in Health AI is pending WSCUC accreditation.

Training & Curriculum

The program takes an active learning approach to Artificial Intelligence (AI), Ethical AI, Machine Learning, Natural Language Processing, Translational AI, Computational Biomedicine, Devices and Wearables, and Imaging AI, with a strong emphasis in one-to-one mentoring.

Application Information

We encourage highly motivated individuals who have completed a bachelor’s degree in quantitative scientific disciplines such as bioinformatics, computational biology, computer science, engineering or mathematics, with a demonstrated interest in health research, to submit an application in the Fall for admission the following year.

Key Deadlines

Message From the Program Director

The Cedars-Sinai PhD in Health Artificial Intelligence program is designed around a learner-centered philosophy: you bring your own knowledge, past experiences, education, and ideas – and discover with us how to expand it into exciting new directions. You will have the unique opportunity to work alongside world-renowned experts in AI and healthcare, engaging directly with cutting-edge technologies that are shaping the future of medicine. Our program emphasizes the development of practical skills and real-world problem-solving, ensuring that you are not only prepared to excel in your career but also to lead and innovate."

Professor and Vice Chair for Research and Education, Department of Computational Biomedicine

Faculty & Administration

An accomplished team of scientists, educators and innovators lead and coordinate the myriad activities of the PhD program in Health Artificial Intelligence.

Have Questions or Need Help?

If you have questions or wish to learn more about the PhD program in Health AI, call us or send a message.

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Artificial intelligence and natural language processing

Making sense of human communication is at the heart of our work in natural language processing and Artificial Intelligence. Research in these areas, particularly the success of deep learning, is leading to unprecedented improvements in applications such as text understanding, information retrieval, and human language interfaces.

Our research also aims to develop a deeper understanding of how humans use language. We investigate this with our work in natural language generation, ambiguity analysis, and dialogue systems. We apply the same techniques to understanding music to generate adaptive soundtracks for computer games automatically.

Entry requirements

Minimum 2:1 undergraduate degree (or equivalent). If you are not a UK citizen, you may need to prove your knowledge of English .

Potential research projects

• Natural language generation
• Dialogue systems and information flow
• Ambiguity in text
• Automatic music composition
• Natural language processing in educational applications
• Information retrieval
• Neurobehavioural models of perceptual uncertainty

Potential supervisors

• Dr Jane Bromley
• Professor Robin Laney
• Dr Adam Linson
• Dr Paul Piwek
• Dr Neil Smith
• Dr Alistair Willis

Some of our research students are funded via Doctoral Training Partnership EPSRC and the STEM Faculty; others are self-funded.

For detailed information about fees and funding, visit  Fees and studentships .

To see current funded studentship vacancies across all research areas, see Current studentships .

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Email: STEM CC PHD

Please review the application process if you want to apply for this research topic.

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Course type

Qualification, university name, phd degrees in artificial intelligence (ai).

16 degrees at 13 universities in the UK.

Customise your search

Select the start date, qualification, and how you want to study

About Postgraduate Artificial Intelligence (AI)

Artificial Intelligence (AI) is a branch of computer science focused on creating machines that can perform tasks with a simulated human intelligence. AI builds computers which can learn, reason, problem-solve and understand natural language. It is a relatively new and rapidly advancing field with a huge range of practical applications from speech recognition and image processing to autonomous vehicles and virtual assistants.

Currently there are 15 artificial intelligencePhD programmes offered at UK universities and entry requirements typically include a strong background in computer science, software engineering or a related field, along with a well-constructed research proposal, which should address an important or underdeveloped aspect of AI and will form the basis for your PhD studies.

The PhD course itself will have a duration of around three to six years and will primarily be centered around your research proposal which you’ll develop under the supervision of an academic tutor.

What to Expect

For a PhD, you can expect to be doing a lot of self-driven study. You may be part of a research team or a member of a laboratory or engineering workshop, but a significant amount of your time will still be spent researching material for your thesis and developing your project. AI is a highly versatile field and you might find yourself working in machine learning, robotics, natural language processing, computational intelligence, or even the ethics behind striving to create intelligent machines and what effects this might have on human society.

You’ll present your research periodically; however, the main assessment is your PhD dissertation, which after submitting, you will be required to defend orally in front of a panel of academics. Once this is complete, you’ll be qualified as a Doctor of Philosophy in artificial intelligence and will be ready for roles in AI research, data science, industry or academia.

Related subjects:

• PhD Artificial Intelligence (AI)
• PhD Animation Software
• PhD Bioinformatics
• PhD Business Information Systems
• PhD Computer Animation
• PhD Computer Architectures
• PhD Computer Communications and Networking
• PhD Computer Cybernetics
• PhD Computer Games Design
• PhD Computer Graphics
• PhD Computer Network Components
• PhD Computer Science and Information Technology
• PhD Computer Security Systems
• PhD Computer Systems
• PhD Computing Methodologies
• PhD Data Science
• PhD Expert Systems
• PhD Geographical Information Systems Software
• PhD Graphics And Multimedia Software
• PhD Health Informatics
• PhD Human Computer Interface Development
• PhD Image Processing
• PhD Informatics
• PhD Information Management
• PhD Information Security
• PhD Information Systems
• PhD Information Technology
• PhD Information Work and Information Use
• PhD Internet Security Systems
• PhD Internet Systems
• PhD Knowledge Management Systems
• PhD Librarianship and Library Management
• PhD Libraries and Librarianship
• PhD Mobile Computing
• PhD Modelling and Simulation Systems
• PhD Multimedia
• PhD Network Systems Management
• PhD Network Systems Management Software
• PhD Pattern Recognition
• PhD Software Development
• PhD Software Engineering
• PhD Software Testing
• PhD Software for Specific Subjects and Industries
• PhD Systems Analysis and Design
• PhD Using Software

• Course title (A-Z)
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• Price: low - high

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Qualification:

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Review for GWU Online PhD In Artificial Intelligence and Machine Learning?

Hello, I would like some review for:

George Washington University (GWU)'s ONLINE PhD in Artificial Intelligence and Machine Learning .

BASIC info from the GWU's program website and the fyler pdf: https://seasonline.gwu.edu/doctoral-degrees/ai-and-machine-learning/

https://seasonline.gwu.edu/wp-content/uploads/2023/06/DA1_Flyer_6.15.23.pdf

Duration: 2 years ONLINE, Saturday class 9am-4pm (Eastern time). First year (24 credits) for 8 courses in AI, ML, and second year (24 credits) for a praxis research.

Estimated tuition: $1750/credit x 48 credits = $84000.

Admission requirement: Master's degree in STEM with min GPA 3.2. NO GRE. NO letter of recommendation. English requirement (TOEFL) but may be exempt if applicable.

Performance requirement: no course below B- otherwise terminated

Request for review/comment for the program:

Rigorness of the program. I have heard about several universities that their quality is compromised when on-site programs are converted to online. Not sure about GWU, and even an online PhD program, which is rare.

Quality of courses. The syllabus of the 8 courses are not made public, but seems not deep, just: basic AI, ML, DE, Statistics + 1 course in Deep Learning + 1 course for all Computer Vision, Natural Language Processing and Reinforcement Learning combined (!) + 1 course for political issues in AI. Further more, i don't know if in each course, they have Teaching Assistants for grading students' assignment. Or even if they have assignments for coding, solving problems or just writing essays/review papers.

Praxis research?

The reputation of GWU and how big tech companies view GWU phd programs?

Does this degree help you advance in AI/ML?

It seems that the program will be launched the first time in Aug 2023, so any comments about related/similar programs of GWU like online PhD programs in system engineering are still extremely helpful.

Overall, is this GWU online phd in AI/ML worth it?

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GW Online Engineering Programs

• Artificial Intelligence and Machine Learning
• Cloud Computing Management
• Cybersecurity Analytics
• Cybersecurity Policy & Compliance
• Electrical Engineering
• Engineering Management
• Systems Engineering
• Policies & Procedures
• On-Site International Programs
• Artificial Intelligence & Machine Learning (D.Eng.)
• Cybersecurity Analytics (D.Eng.)
• Engineering Management (D.Eng.)
• Systems Engineering (Ph.D.)
• Degrees Offered
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• Student Resources
• Application Process

Apply for Admission

Online Doctor of Philosophy in Systems Engineering

The next cohort begins in August 2025.  Applications will open in January 2025.

Sign up for Info Session

Program Flyer

Program Description

The online Ph.D. in Systems Engineering develops a deep expertise in designing, analyzing, and managing complex systems for students seeking advanced academic study. This program is designed for individuals who aim to conduct groundbreaking research in the field. They contribute to developing innovative methodologies and solutions for systems engineering challenges. The program emphasizes a multidisciplinary approach, integrating concepts from engineering, management, and computer science.

Doctoral candidates are expected to engage in substantial research projects. These projects culminate in a dissertation that adds original knowledge or understanding to the field of systems engineering. This research is typically characterized by a strong analytical and problem-solving focus, addressing issues in areas such as infrastructure, healthcare, transportation, or environmental systems. Graduates of the program are well-prepared for careers in academia or research institutions. They can also excel in high-level consultancy roles, applying their expertise to solve complex systems problems, influence policy, or educate the next generation of systems engineers.

The program consists of a minimum of 54 credit hours divided into two stages: the classroom phase (24 credit hours) and the research phase (30 credit hours). During the research phase, the student writes and defends research on a topic related to Systems Engineering. The topic is selected by the student and approved by the research advising committee.

EMSE 6420 Uncertainty Analysis in Cost Engineering:  Basic skills for building probability models to perform meaningful engineering economic studies, financial feasibility assessments, and cost uncertainty analysis in the planning phase of engineering projects. (3 credit hours) 

EMSE 6760 Discrete Systems Simulation:  Simulation of discrete stochastic models. Simulation languages. Random-number/ random-variate generation. Statistical design and analysis of experiments, terminating/nonterminating simulations; and comparison of system designs. Input distributions, variance reduction, validation of models. (3 credit hours) 

EMSE 6765 Data Analysis for Engineers and Scientists:  Design of experiments and data collection. Regression, correlation, and prediction. Multivariate analysis, data pooling, data compression. Model validation. (3 credit hours) 

EMSE 6807 Advanced Systems Engineering:  Analysis of advanced systems engineering topics; system lifecycle models, INCOSE Vision 2025, requirements types and processes, architectural design processes and frameworks, DoDAF artifacts, enterprise architecture and enterprise systems engineering, complex adaptive systems (CAS), modeling languages and SysML, and Model Based Systems Engineering (MBSE). Applications of systems engineering tools and techniques. EMSE 6817 Model-Based Systems Engineering. Model-based systems engineering (MBSE) and its derivative, evidence-based systems engineering (EBSE), are techniques with strong potential for improving the technical integrity of complex systems. The foundation to these model- and research-based techniques for system definition and analysis as applied to life- cycle SE. Practical applications. (3 credit hours) 

EMSE 6848 Systems of Systems:  Complex systems engineering in terms of systems of systems (SoS); theoretical and practical instances of SoS; application of life cycle systems engineering processes; various types of SoS and the challenges to be faced to ensure their acquisition and technical integrity. (3 credit hours)

EMSE 6850 Quantitative Models in Systems Engineering:  Quantitative modeling techniques and their application to decision making in systems engineering. Linear, integer, and nonlinear optimization models. Stochastic models: inventory control, queuing systems, and regression analysis. Elements of Monte Carlo and discrete event system simulation. (3 credit hours) 

EMSE 8000 Research Formulation in Systems Engineering:  Doctoral seminar designed to give students their first exposure to the process of formulating and executing empirical research. Class format includes discussion, field experiments, data analysis, and theorizing. Study of core concepts in building theory from empirical data and classic works in technically oriented management theory. Participants design and execute a research project. (3 credit hours) 

EMSE 8999 Dissertation Research:  Independent research in systems engineering culminating in the writing of the dissertation and successful defense of the Dissertation. (30 credit hours)

Classroom courses last 10 weeks each and meet on Saturday mornings from 9:00 AM—12:10 PM and afternoons from 1:00—4:10 PM (all times Eastern). All classes meet live online through synchronous distance learning technologies (Zoom). All classes are recorded and available for viewing within two hours of the lecture. This program is taught in a cohort format in which students take all courses in lock step. Courses cannot be taken out of sequence, attendance at all class meetings is expected, and students must remain continuously enrolled. Leaves of absence are permitted only in the case of a medical or family emergency, or deployment to active military duty.

Upon successful completion of the classroom phase, students are admitted to candidacy for the Ph.D. and will be registered for a minimum total of 30 credit hours (ch) of EMSE 8999 Dissertation Research: 3 ch in Summer 2026, 6 ch Fall 2026, 6 ch Spring 2027, 3 ch Summer 2027, 6 ch Fall 2027, and 6 ch Spring 2028.  More than 30 credit hours of EMSE 8999 may be approved, depending on the candidate’s progress. Approved candidates will be registered for the standard number of ch per semester of extension.   

Tuition is billed at $1650 per credit hour for the 2024-2025 year. A non-refundable tuition deposit of $995, which is applied to tuition in the first semester, is required when the student accepts admission.

Admissions Process

•   Minimum of bachelor’s and master’s degrees in engineering, computer science, mathematics, physics or a closely related field from recognized institutions.
• A minimum graduate level GPA of 3.5 A minimum of two college-level calculus courses passed with grades of B- or better
• Capacity for original scholarship.
• TOEFL, IELTS, Duolingo, or PTE scores are required of all applicants who are not citizens of countries where English is the official language. Learn more on the  International Student page . Test scores may not be more than two years old.  

Note: GRE and GMAT scores are not required.

Please note that our doctoral programs are highly selective; meeting minimum admissions requirements does not guarantee admission. 

• Attach up-to-date Resume
• Attach Statement of Purpose  – In an essay of 250 words or less, state your purpose in undertaking graduate study at The George Washington University. Describe your academic objectives, research interests, and career plans; and discuss your qualifications, including collegiate, professional, and community activities, and any other substantial accomplishments not mentioned.
• Online Engineering Programs  The George Washington University 170 Newport Center Drive Suite 260 Newport Beach, CA 92660

Normally all transcripts must be received before an admission decision is rendered for the Doctor of Philosophy program. 

You will receive emails from us updating you as your application goes through the admissions process.

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Using Artificial Intelligence to Detect Autoimmune Diseases in Women

A q&a with eugenia chock, eugenia chock, md, mph.

Eugenia Chock, MD, MPH , aims to improve the care of women with autoimmune conditions. Current screening for these disorders often results in delayed care, she says.

An assistant professor of medicine (rheumatology, allergy and immunology) at Yale School of Medicine (YSM) and Yale Center for Clinical Investigation Scholar , Chock researches maternal health and offspring outcomes among patients with rheumatic diseases. She is interested in utilizing large clinical datasets to support her work.

Recently, Chock received funding from the Yale Center of Excellence in Regulatory Science and Innovation-Food and Drug Administration Office of Women’s Health to develop the use of AI to remove barriers to diagnosing and addressing autoimmune diseases in women.

In a Q&A, Chock discusses why early diagnosis of autoimmune conditions is important, how machine learning can help, and her hopes for the future of artificial intelligence in medicine.

Why is it important to diagnose autoimmune diseases in women?

In the U.S., approximately 50 million people are affected by autoimmune diseases, and the number is rising. The incidence of systemic lupus erythematosus, for instance, has nearly tripled in the U.S. over the last 40 years.

Eighty percent of individuals affected by autoimmune diseases are women, and many of these diseases have systemic implications, meaning they involve multiple organs. Sex differences influence the onset and severity of these diseases, which can be fatal. Timely diagnosis and treatment can ensure optimal outcomes.

Tell us about your novel machine-learning approach to improve diagnostics in this area.

Many patients are referred to a rheumatologist because they receive a positive antinuclear antibody, or ANA, test result. An ANA test is a very common blood test that screens for autoimmune diseases, particularly lupus and scleroderma. But this test is not perfect. Not all individuals who test positive for ANA have or will develop autoimmune diseases.

Since many people test positive for ANA and are referred to a rheumatologist, the wait lists for these specialists are long. This is a disservice to patients who do have or end up developing an autoimmune disease because their prompt evaluation and care are delayed. In addition, getting a positive test result can cause unnecessary fears among patients, especially if they have to wait a long time to see a specialist.

I am working in collaboration with Na Hong, PhD , instructor of Biomedical Informatics and Data Science at YSM, to use artificial intelligence software to efficiently extract data from electronic health records. Using a machine-learning tool, we’ll identify patients who test positive for ANA and are at risk of developing autoimmune diseases. We’ll also identify patients who have an ANA and don’t develop autoimmunity. All of this is done confidentially in a secure environment. Once we have these two groups of people, we’ll find data points—such as lab test results or medications—in the electronic health records within the Yale ealth system that indicate whether a patient has additional risk factors to develop lupus, scleroderma, or another autoimmune disease down the road.

Once we gather this information from the electronic health records, we’ll apply artificial intelligence software to create an algorithm to help us identify ANA-positive patients who are at higher risk for developing an autoimmune disorder.

What do you hope to accomplish by using AI in medicine?

Currently, we receive many referrals for patients who test positive for ANA, and we don’t know which ones are high risk. I’m hoping that this tool can accurately help physicians identify people—especially women—with autoimmune diseases early on and ensure that they get the appropriate care.

AI in medicine is in its infancy stage. While AI holds much promise, it’s not yet sufficiently refined or reliable to help diagnose or manage medical conditions. It’s just not that sophisticated yet.

My goal is to develop this tool carefully and intelligently to improve the lives of patients and to contribute to the long-term advancement of technology in rheumatology. Once validated by testing in real-world clinical practice, we hope to apply AI for autoimmune disease screening more broadly, improving health care in many health systems nationally.

Yale School of Medicine’s Department of Internal Medicine Section of Rheumatology, Allergy and Immunology is dedicated to providing care for patients with rheumatic, allergic and immunologic disorders; educating future generations of thought leaders in the field; and conducting research into fundamental questions of autoimmunity and immunology. To learn more, visit Rheumatology, Allergy & Immunology.

• Rheumatology
• Internal Medicine
• Autoimmune Diseases
• Data Science
• Food and Drug Administration (FDA)

Featured in this article

• Eugenia Chock, MD, MPH Assistant Professor of Medicine (Rheumatology, Allergy & immunology)
• Na Hong, PhD Instructor of Biomedical Informatics and Data Science