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3 Questions: A new PhD program from the Center for Computational Science and Engineering

Co-directors Youssef Marzouk and Nicolas Hadjiconstantinou describe how the standalone degree aims to train students in cross-cutting aspects of computational science and engineering.

This fall, the Center for Computational Science and Engineering (CCSE), an academic unit in the MIT Schwarzman College of Computing, is introducing a new standalone PhD degree program that will enable students to pursue research in cross-cutting methodological aspects of computational science and engineering. The launch follows approval of the center’s degree program proposal at the May 2023 Institute faculty meeting.

Doctoral-level graduate study in computational science and engineering (CSE) at MIT has, for the past decade, been offered through an interdisciplinary program in which CSE students are admitted to one of eight participating academic departments in the School of Engineering or School of Science. While this model adds a strong disciplinary component to students’ education, the rapid growth of the CSE field and the establishment of the MIT Schwarzman College of Computing have prompted an exciting expansion of MIT’s graduate-level offerings in computation.

The new degree, offered by the college, will run alongside MIT’s existing interdisciplinary offerings in CSE, complementing these doctoral training programs and preparing students to contribute to the leading edge of the field. Here, CCSE co-directors Youssef Marzouk and Nicolas Hadjiconstantinou discuss the standalone program and how they expect it to elevate the visibility and impact of CSE research and education at MIT.

Q: What is computational science and engineering?

Marzouk: Computational science and engineering focuses on the development and analysis of state-of-the-art methods for computation and their innovative application to problems of science and engineering interest. It has intellectual foundations in applied mathematics, statistics, and computer science, and touches the full range of science and engineering disciplines. Yet, it synthesizes these foundations into a discipline of its own — one that links the digital and physical worlds. It’s an exciting and evolving multidisciplinary field.

Hadjiconstantinou: Examples of CSE research happening at MIT include modeling and simulation techniques, the underlying computational mathematics, and data-driven modeling of physical systems. Computational statistics and scientific machine learning have become prominent threads within CSE, joining high-performance computing, mathematically-oriented programming languages, and their broader links to algorithms and software. Application domains include energy, environment and climate, materials, health, transportation, autonomy, and aerospace, among others. Some of our researchers focus on general and widely applicable methodology, while others choose to focus on methods and algorithms motivated by a specific domain of application.

Q: What was the motivation behind creating a standalone PhD program?

Marzouk: The new degree focuses on a particular class of students whose background and interests are primarily in CSE methodology, in a manner that cuts across the disciplinary research structure represented by our current “with-departments” degree program. There is a strong research demand for such methodologically-focused students among CCSE faculty and MIT faculty in general. Our objective is to create a targeted, coherent degree program in this field that, alongside our other thriving CSE offerings, will create the leading environment for top CSE students worldwide.

Hadjiconstantinou: One of CCSE’s most important functions is to recruit exceptional students who are trained in and want to work in computational science and engineering. Experience with our CSE master’s program suggests that students with a strong background and interests in the discipline prefer to apply to a pure CSE program for their graduate studies. The standalone degree aims to bring these students to MIT and make them available to faculty across the Institute.

Q: How will this impact computing education and research at MIT?  

Hadjiconstantinou: We believe that offering a standalone PhD program in CSE alongside the existing “with-departments” programs will significantly strengthen MIT’s graduate programs in computing. In particular, it will strengthen the methodological core of CSE research and education at MIT, while continuing to support the disciplinary-flavored CSE work taking place in our participating departments, which include Aeronautics and Astronautics; Chemical Engineering; Civil and Environmental Engineering; Materials Science and Engineering; Mechanical Engineering; Nuclear Science and Engineering; Earth, Atmospheric and Planetary Sciences; and Mathematics. Together, these programs will create a stronger CSE student cohort and facilitate deeper exchanges between the college and other units at MIT.

Marzouk: In a broader sense, the new program is designed to help realize one of the key opportunities presented by the college, which is to create a richer variety of graduate degrees in computation and to involve as many faculty and units in these educational endeavors as possible. The standalone CSE PhD will join other distinguished doctoral programs of the college — such as the Department of Electrical Engineering and Computer Science PhD; the Operations Research Center PhD; and the Interdisciplinary Doctoral Program in Statistics and the Social and Engineering Systems PhD within the Institute for Data, Systems, and Society — and grow in a way that is informed by them. The confluence of these academic programs, and natural synergies among them, will make MIT quite unique.

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Electrical Engineering and Computer Science

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617-253-4603 [email protected]

Website: Electrical Engineering and Computer Science

Application Opens: September 16

Deadline: December 15 at 11:59 PM Eastern Time

Fee: $75.00

Terms of Enrollment

Master of Engineering in Electrical Engineering and Computer Science (MEng)*

Interdisciplinary Programs

Standardized tests.

Graduate Record Examination (GRE)

• Not required

International English Language Testing System (IELTS)

• Minimum score required: 7
• Electronic scores send to: MIT Graduate Admissions

Test of English as a Foreign Language (TOEFL)

• Minimum score required: 100 (iBT) 600 (PBT)
• Institute code: 3514
• Department code: 78 or 66

IELTS exam is preferred over the TOEFL. Waiver of TOEFL/IELTS may be available.

Areas of Research

• Artificial Intelligence
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• Communications
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• Electromagnetics, Energy, and Power
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• Theoretical Computer Science

Financial Support

In the EECS PhD program, students are supported with a fellowship, research assistantship or teaching assistantship. The financial support provides full tuition, a monthly living stipend and medical insurance. When needed, additional departmental support is available. 

Decisions on support are made after decisions on admission and are based on the information supplied in the application for admission. Any newly admitted student will automatically be considered for Department fellowships and assistantship support. Newly admitted students are also encouraged to apply to outside government and private agencies for fellowship support. Please see the EECS website for more information.

Application Requirements

• Online application
• Statement of objectives
• Three letters of recommendation
• Transcripts
• English proficiency exam scores

Special Instructions

*The Master of Engineering degrees are available to MIT undergraduates only.

**The Master of Science degree is required of students pursuing a doctoral degree. If you do not have a master’s degree when you apply, you will receive that degree first before proceeding to the PhD. A terminal master’s degree is not offered.

Applicants should not send published papers or theses. Admitted students will be required to submit official transcript(s) to the EECS Graduate Office.

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Doctoral Programs in Computational Science and Engineering

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CS PhD Course Guidelines

The following program guidelines (a.k.a model pogram) serve as a starting point for a discussion with the faculty about areas of interest.   This description of the Computer Science PhD course guidelines augments the school-wide  PhD course requirements .   Students should make themselves familiar with both.

Course Guidelines for Ph.D. Students in Computer Science

We expect students to obtain broad knowledge of computer science by taking graduate level courses in a variety of sub-areas in computer science, such as systems, networking, databases, algorithms, complexity, hardware, human-computer interaction, graphics, or programming languages.

Within our school, CS courses are roughly organized according to sub-area by their middle digit, so we expect students to take courses in a minimum of three distinct sub-areas, one of which should be theory (denoted by the middle digit of 2, or CS 231). Theory is specifically required as we expect all students to obtain some background in the mathematical foundations that underlie computer science. The intention is not only to give breadth to students, but to ensure cross-fertilization across different sub-disciplines in Computer Science.

Just as we expect all students obtaining a Ph.D. to have experience with the theoretical foundations of computer science, we expect all students to have some knowledge of how to build large software or hardware systems , on the order of thousands of lines of code, or the equivalent complexity in hardware. That experience may be evidenced by coursework or by a project submitted to the CHD for examination. In almost all cases a course numbered CS 26x or CS 24x will satisfy the requirement (exceptions will be noted in the course description on my.harvard). Students may also petition to use CS 161 for this requirement.   For projects in other courses, research projects, or projects done in internships the student is expected to write a note explaining the project, include a link to any relevant artifacts or outcomes, describe the student's individual contribution, and where appropriate obtain a note from their advisor, their class instructor, or their supervisors confirming their contributions.  The project must include learning about systems concepts, and not just writing many lines of code.   Students hoping to invoke the non-CS24x/26x/161 option must consult with  Prof. Mickens ,  Prof, Kung,  or  Prof. Idreos  well in advance of submitting their Program Plan to the CHD.  

Computer science is an applied science, with connections to many fields. Learning about and connecting computer science to other fields is a key part of an advanced education in computer science. These connections may introduce relevant background, or they may provide an outlet for developing new applications.

For example, mathematics courses may be appropriate for someone working in theory, linguistics courses may be appropriate for someone working in computational linguistics, economics courses may be appropriate for those working in algorithmic economics, electrical engineering courses may be appropriate for those working in circuit design, and design courses may be appropriate for someone working in user interfaces.

Requirements

The Graduate School of Arts & Sciences (GSAS) requires all Ph.D. students to complete 16 half-courses (“courses”, i.e., for 4 units of credit) to complete their degree. Of those 16 courses, a Ph.D. in Computer Science requires 10 letter-graded courses. (The remaining 6 courses are often 300-level research courses or other undergraduate or graduate coursework beyond the 10 required courses.)

The requirements for the 10 letter-graded courses are as follows:

• Of the 7 technical courses, at least 3 must be 200-level Computer Science courses, with 3 different middle digits (from the set 2,3,4,5,6,7,8), and with one of these three courses either having a middle digit of 2 or being CS 231 (i.e., a “theory” course).   Note that CS courses with a middle digit of 0 are valid technical courses, but do not contribute to the breadth requirement.
• At least 5 of the 8 disciplinary courses must be SEAS or SEAS-equivalent 200-level courses. A “SEAS equivalent” course is a course taught by a SEAS faculty member in another FAS department. 
• For any MIT course taken, the student must provide justification why the MIT course is necessary (i.e. SEAS does not offer the topic, the SEAS course has not been offered in recent years, etc.). MIT courses do not count as part of the 5 200-level SEAS/SEAS-equivalent courses. 
• 2 of the 10 courses must constitute an external minor (referred to as "breadth" courses in the SEAS “ Policies of the Committee on Higher Degrees [CHD] ”) in an area outside of computer science. These courses should be clearly related; generally, this will mean the two courses are in the same discipline, although this is not mandatory. These courses must be distinct from the 8 disciplinary courses referenced above.
• Students must demonstrate practical competence by building a large software or hardware system during the course of their graduate studies. This requirement will generally be met through a class project, but it can also be met through work done in the course of a summer internship, or in the course of research.
• In particular, for Computer Science graduate degrees, Applied Computation courses may be counted as 100-level courses, not 200-level courses.
• Up to 2 of the 10 courses can be 299r courses, but only 1 of the up to 2 allowed 299r courses can count toward the 8 disciplinary courses. 299r courses do not count toward the 5 200-level SEAS/SEAS-equivalent courses. If two 299r’s are taken, they can be with the same faculty but the topics must be sufficiently different.
• A maximum of 3 graduate-level transfer classes are allowed to count towards the 10 course requirement.
• All CS Ph.D. program plans must adhere to the SEAS-wide Ph.D. requirements, which are stated in the SEAS Policies of the Committee on Higher Degrees (CHD) . These SEAS-wide requirements are included in the items listed above, though students are encouraged to read the CHD document if there are questions, as the CHD document provides further explanation/detail on several of the items above.
• All program plans must be approved by the CHD. Exceptions to any of these requirements require a detailed written explanation of the reasoning for the exception from the student and the student’s research advisor. Exceptions can only be approved by the CHD, and generally exceptions will only be given for unusual circumstances specific to the student’s research program.

Requirement Notes

• Courses below the 100-level are not suitable for graduate credit.
• For students who were required to take it, CS 2091/2092 (formerly CS 290a/b or 290hfa/hfb may be included as one of the 10 courses but it does not count toward the 200-level CS or SEAS/SEAS-equivalent course requirements nor toward the SM en route to the PhD.

Your program plan  must always comply  with both our school's General Requirements, in addition to complying with the specific requirements for Computer Science. All program plans must be approved by the Committee on Higher Degrees [CHD]. Exceptions to the requirements can only be approved by the CHD, and generally will only be given for unusual circumstances specific to the student’s research program

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Admissions Requirements

The following are general requirements you should meet to apply to the MIT Sloan PhD Program. Complete instructions concerning application requirements are available in the online application.

General Requirements

• Bachelor's degree or equivalent
• A strong quantitative background (the Accounting group requires calculus)
• Exposure to microeconomics and macroeconomics (the Accounting group requires microeconomics)

A Guide to Business PhD Applications by Abhishek Nagaraj (PhD 2016) may be of interest.

Application Components

Statement of purpose.

Your written statement is your chance to convince the admissions committee that you will do excellent doctoral work and that you have the promise to have a successful career as an academic researcher. 

GMAT/GRE Scores

We require either a valid GMAT or valid GRE score. At-home testing is allowed. Your unofficial score report from the testing institution is sufficient for application. If you are admitted to the program, you will be required to submit your official test score for verification.    

We do not have a minimum score requirement. We do not offer test waivers. Registration information for the GMAT (code X5X-QS-21) and GRE (code 3510) may be obtained at www.mba.com and www.ets.org respectively.

TOEFL/IELTS Scores

We require either a valid TOEFL (minimum score 577 PBT/90 IBT ) or valid IELTS (minimum score 7) for all non-native English speakers. Your unofficial score report from the testing institution is sufficient for application. If you are admitted to the program, you will be required to submit your official test score for verification.    Registration information for TOEFL (code 3510) and IELTS may be obtained at www.toefl.org and www.ielts.org respectively.

The TOEFL/IELTS test requirement is waived only if you meet one of the following criteria:

• You are a native English speaker.
• You attended all years of an undergraduate program conducted solely in English, and are a graduate of that program.

Please do not contact the PhD Program regarding waivers, as none will be discussed. If, upon review, the faculty are interested in your application with a missing required TOEFL or IELTS score, we may contact you at that time to request a score.

Transcripts

We require unofficial copies of transcripts for each college or university you have attended, even if no degree was awarded. If these transcripts are in a language other than English, we also require a copy of a certified translation. In addition, you will be asked to list the five most relevant courses you have taken.

Letters of Recommendation

We require three letters of recommendation. Academic letters are preferred, especially those providing evidence of research potential. We allow for an optional  fourth recommendation, but no more than four recommendations are allowed.

Your resume should be no more than two pages. You may chose to include teaching, professional experience, research experience, publications, and other accomplishments in outside activities.

Writing Sample(s)

Applicants are encouraged to submit a writing sample. For applicants to the Finance group, a writing sample is required. There are no specific guidelines for your writing sample. Possible options include (but are not limited to) essays, masters’ theses, capstone projects, or research papers.

Video Essay

A video essay is required for the Accounting research group and optional for the Marketing and System Dynamics research groups. The essay is a short and informal video answering why you selected this research group and a time where you creatively solved a problem. The video can be recorded with your phone or computer, and should range from 2 to 5 minutes in length. There is no attention — zero emphasis! — on the production value of your video.  

Nondiscrimination Policy: The Massachusetts Institute of Technology is committed to the principle of equal opportunity in education and employment. For complete text of MIT’s Nondiscrimination Statement, please click  here .

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• Media Arts and Sciences (MAS)
• Military Science (MS)
• Music and Theater Arts (Course 21M)
• Naval Science (NS)
• Science, Technology, and Society (STS)
• Special Programs
• Supply Chain Management (SCM)
• Urban Studies and Planning (Course 11)
• Women's and Gender Studies (WGS)

Master of Science in Computational Science and Engineering

Restricted electives.

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