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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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Doctoral Degrees

A doctoral degree requires the satisfactory completion of an approved program of advanced study and original research of high quality..

Please note that the Doctor of Philosophy (PhD) and Doctor of Science (ScD) degrees are awarded interchangeably by all departments in the School of Engineering and the School of Science, except in the fields of biology, cognitive science, neuroscience, medical engineering, and medical physics. This means that, excepting the departments outlined above, the coursework and expectations to earn a Doctor of Philosophy and for a Doctor of Science degree from these schools are generally the same. Doctoral students may choose which degree they wish to complete.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Some departments require a doctoral candidate to take a “minor” program outside of the student’s principal field of study; if you wish to apply to one of these departments, please consider additional fields you may like to pursue.

Below is a list of programs and departments that offer doctoral-level degrees.

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The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different MIT laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include behavioral genetics and genomics; bioengineering and neuroengineering; biological networks and machine learning; cancer systems biology; cellular biophysics; chemical biology and metabolomics; evolutionary and computational biology; microbiology and systems ecology; molecular biophysics and structural biology; precision medicine and medical genomics; quantitative imaging; regulatory genomics, epigenomics, and proteomics; single cell manipulations and measurement; stem cell and developmental systems biology; synthetic biology and biological design; and systems immunology.

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects are comprised of modern biology, computational biology, and a literature-based exploration of current research frontiers and paradigms, which is required of all first-year students in the program . Students also participate in three research rotations of one to two months' duration during their first year to expose them to a range of research activities in computation and systems biology, and to assist them in choosing a lab. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

To develop breadth and depth, add to the base of the diversified core, and contribute strength in areas related to their interest and research direction, students must take four advanced electives. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects

CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research

Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fifth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams

In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research

Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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Dear prospective applicant,

Thank you for your interest in graduate study in EECS.

For information on EECS, please visit our web page:  http://www-eecs.mit.edu/ . The Electrical Engineering and Computer Science Department does NOT require GRE scores for admission purposes. Admission is determined by GPA (Grade Point Average) although there is not an official cut-off, letters of recommendation (we need three of them) and a “Statement of Objectives” in which you write an essay detailing your research interests. For more information about writing a Statement of Objectives, see  this article from the MIT EECS Communication Lab . A very strong background in math, physics, engineering, or computer science is a necessity. Admission for the limited number of openings is extremely competitive and each year we are forced to turn down hundreds of applicants with excellent credentials. Since we do not have a terminal Master’s program in EECS, everyone must apply for PhD. Applicants who gain admission pursue the Master’s degree on the way to the PhD. If a student already has a Master’s from another school, there is no need to do another Master’s degree here at MIT.

We use an online application system which you can access by going to  https://gradapply.mit.edu/eecs/apply . The online system becomes available September 15th.

Decisions on financial aid are made after admission decisions are reached. International students are eligible for research assistantships which pay a monthly stipend and full tuition. Research supervisors are determined after admission decisions are reached or shortly after registering in EECS in the Fall. Admitted students are also eligible for certain fellowships.

International students must take the TOEFL exam and earn at least a score of 100 (internet-based). In some cases, the TOEFL can be waived; such as if you’ve been in U.S. for at least two years, or if your country’s first language is English. International students can also take the IELTS exam if the TOEFL is not available to you. We need to see a score of ‘7’ on this test. It also can be waived for the same reasons as the TOEFL.

We do NOT offer spring term admission. The deadline for applying for Fall Term 2025 is December 15, 2024. The online application will be available between September 15, 2024 and December 15, 2024. 

Good luck with your application!

Doctoral Programs in Computational Science and Engineering

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1. Undergraduate Admissions

• Apply to MIT as an undergrad  ( Labs like CSAIL do not directly admit students)
• Apply to MIT's summer programs
• Current MIT undergrads: do CSAIL research via the  Undergraduate Research Opportunities Program  (UROP)

2. Graduate Admissions

CSAIL does not directly admit students. Instead, students apply directly to specific departments, like  Electrical Engineering & Computer Science , Mathematics , Aeronautics and Astronautics and  Mechanical Engineering . 

Deadlines for most programs are December 15. Engineering master’s students at MIT can also  do research assistantships   at CSAIL.

3. Postdoctoral Opportunities

Potential postdocs should  explore our research  and reach out directly to the principal investigator you’d like to work with!

NOTE: CSAIL doesn't generally accept interns or research assistants, especially non-MIT students. In the rare event that a faculty member chooses to take one on, preference is given to MIT students.

Computer Science - Doctor of Philosophy (PhD)

Mathematics 3 (M3) Building on Waterloo's Campus

Pursue research and expand your learning with the PhD in Computer Science.

In this program, you'll work with a supervisor to develop a thesis and conduct meaningful research that expands the scope of your graduate work, preparing you to enter a career in academia, research or private industry.  

You'll also gain industry experience for in-demand careers with the option to apply to transfer to the PhD in Computer Science – Internship program after completing at least one academic term. 

The MMath in Computer Science is offered through the Cheriton School of Computer Science, which has been ranked number one nationally four years in a row based on program and research reputation according to the Maclean’s 2024 university rankings. Waterloo and the Cheriton School are among the top 25 universities internationally for computer science according to the 2023, 2022 and 2021 Quacquarelli Symonds worldwide university subject rankings, and attract exceptional students from all over the world.    

Program highlights

The Cheriton School of Computer Science has been ranked number one nationally four years in a row based on program and research reputation according to the Maclean’s 2024 university rankings. 

Learn from internationally acclaimed researchers 

Access research-intensive lab spaces 

Opportunities to publish your work and present at top conferences 

Own your work. Waterloo’s intellectual property (IP) policy means that everything you create is yours to keep  

Research areas

• Algorithms and Complexity
• Artificial Intelligence
• Bioinformatics
• Computer Algebra and Symbolic Computation
• Computer Graphics
• Cryptography, Security and Privacy
• Formal Methods
• Health Informatics
• Human-Computer Interaction
• Information Retrieval
• Machine Learning
• Programming Languages
• Quantum Computing
• Scientific Computing
• Software Engineering
• Systems and Networking

Program overview

Department/School : David R. Cheriton School of Computer Science Faculty : Faculty of Mathematics Admit term(s) : Fall (September - December), Winter (January - April), Spring (May - August) Delivery mode : On-campus Program type : Doctoral, Research Length of program : 48 months (full-time) Registration option(s) : Full-time, Part-time Study option(s) : Thesis

Application deadlines

•  December 1 (for admission in September of the following year)
•  June 1 (for admission in January of the following year)
•  October 1 (for admission in May of the following year)

Key contacts

Computer Science Graduate Office

There's a lot of opportunities, so it’s important to do what you like and just be open to the possibilities. Shenghao Yang, Computer Science, PhD

Supervisors

• Review the  finding a supervisor resources
• Before applying to the program, students are strongly advised to establish contact with potential supervisors

Admission requirements

• A Master's degree in Computer Science with a 78% average.
• Student with an undergraduate degree in Computer Science may apply for admission directly to the PhD program. Successful applicants will have an outstanding academic record, breadth of knowledge in computer science, and strong letters of recommendation.
• PhD applicants may be admitted into the Master of Mathematics (MMath) program. Like all MMath students, they will have the option to transfer into the PhD program before completing the master's thesis if their performance warrants.

Degree requirements

• Review the degree requirements in the Graduate Studies Academic Calendar, including the courses that you can anticipate taking as part of completing the degree
• Check out Waterloo's institutional thesis repository - UWspace to see recent submissions from the David R. Cheriton School of Computer Science graduate students

Application materials

• The SIF contains questions specific to your program, typically about why you want to enrol and your experience in that field. Review the  application documents web page  for more information about this requirement
• If a statement or letter is required by your program, review the  writing your personal statement resources  for helpful tips and tricks on completion

Transcript(s)

• Three  references  are required; at least two academic
• TOEFL 93 (writing 22, speaking 22), IELTS 6.5 (writing 6.0, speaking 6.5)

Tuition and fees

Visit the  graduate program tuition page  on the Finance website to determine the tuition and incidental fees per term for your program

Review living costs and housing

Review the   funding graduate school resources   for graduate students

Graduate Study at SHASS

World-class graduate studies.

SHASS offers five doctoral and four master’s programs.

Doctoral programs

Our top-ranked PhD program sets the standard for graduate economics training across the country. Graduate students work closely with our world-class faculty to develop their own research and prepare to make impactful contributions to the field.

Our doctoral program enrolls 20-24 full-time students each year and students complete their degree in five to six years. Students undertake core coursework in microeconomic theory, macroeconomics, and econometrics, and are expected to complete two major and two minor fields in economics. Beyond the classroom, doctoral students work in close collaboration with faculty to develop their research capabilities, gaining hands-on experience in both theoretical and empirical projects.

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History, Anthropology, and STS (HASTS)

The doctoral program in History, Anthropology, and Science, Technology, and Society (HASTS) at MIT, founded in 1988, is a unique interdisciplinary academic community devoted to studying the social, cultural, and political life of science and technology. HASTS faculty work with students to develop original scholarship on the historical foundations and contemporary implications of scientific and technological knowledge and practice.

As a culmination of their work, HASTS students complete dissertations that intervene in scholarly and public conversations about the role of science in society. After graduation, students go on to careers in academia, public service, and private industry.

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Linguistics

Our 5-year PhD program is designed to introduce students to the basic concepts and results of research in generative linguistics, so that they can begin productively contributing to the department’s research activities. We have found that the best way to achieve this goal is for students to work from the very beginning on problems that are relevant to real-life research.

The program is rigorous and quite demanding of students’ time and energy. A high level of commitment and concentration is required to complete it successfully. The program also contains a relatively large number of required courses. We have found that this extra effort pays off in the long run, since students are exposed to a richer mix of research topics and methods. This also means that our students attain a high level of competence in more than one area, and thus qualify for academic and other positions in more than one specialty.

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From scallop fishing in New Bedford to deforestation in the tropics, “our goal is to get some empirical traction on the problem,” says Economics PhD student Aaron Berman.

Our program provides subjects and seminars in such traditional areas as logic, ethics, metaphysics, epistemology, philosophy of science, philosophy of language, philosophy of mind, aesthetics, social and political philosophy, and history of philosophy. Interest in philosophical problems arising from other disciplines, such as linguistics, psychology, mathematics and physics, is also encouraged.

Before beginning dissertation research, students are required to take two years of coursework, including a proseminar in contemporary philosophy that all students must complete in their first year of graduate study. Students are also required to write a fifth term pre-dissertation paper and demonstrate competence in the following areas: value theory, logic and the history of philosophy.

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Political Science

Our doctoral students are advancing political science as a discipline. They explore the empirical phenomena that produce new scholarly insights—insights that improve the way governments and societies function. As a result, MIT Political Science graduates are sought after for top teaching and research positions in the U.S. and abroad.

The MIT PhD in Political Science requires preparation in two of these major fields: American Politics, Comparative Politics, International Relations, Models and Methods, Political Economy, or Security Studies. We recommend that you take a broad array of courses across your two major fields.

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Philosophy doctoral student Abe Mathew is both studying philosophy and questioning some of its deeply-held ideas.

Master’s programs

Data, economics, and design of policy.

The international fight against poverty is more data driven than ever before. Producing and understanding rigorous evidence has become increasingly critical for those seeking to affect change globally, but opportunities to acquire these skills remain limited.

As the first master’s program to be offered by MIT’s Department of Economics, the master’s program in Data, Economics, and Design of Policy (DEDP) is designed to meet this rising demand. Jointly run by the Economics Department and the Abdul Latif Jameel Poverty Action Lab (J-PAL ), the program equips development professionals from across the globe with the practical skills and theoretical knowledge needed to tackle some of the world’s most pressing challenges.

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MIT Indigenous Language Initiative (Linguistics)

The MIT Indigenous Languages Initiative is a special master’s program in linguistics for members of communities whose languages are threatened. The goal of the program is to provide its graduates with the linguistic knowledge that will help them in efforts to keep their communities’ languages alive.

In addition, the MIT Indigenous Language Initiative offers expanded opportunities for students and faculty to become involved in indigenous and endangered languages. They do this through working with native speaker linguists in the master’s program and also with outside groups.

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The MIT Political Science master’s program prepares students to uncover essential insights into the workings of societies and governments in the 21st century. Master’s students develop the skills and knowledge to evaluate and promote effective public policies.

The one-year MIT Master of Science in Political Science is designed for students who want to build proficiency in applied research so that they can pursue successful careers in government, business, and public policy. Students interested in an academic career should read more about the PhD in Political Science.

Science Writing

The MIT Graduate Program in Science Writing (GPSW) is one of the world’s premier master’s programs in science journalism and communication. Set within a community of world-renowned scientists, cutting-edge facilities, and groundbreaking research, our one-year program focuses on introducing students to science communication across a broad range of media, including news and feature reporting, podcasting, data journalism, and documentary film.

During their year here, students learn fundamental research and reporting skills and produce publishable works of print, audio, video, and interactive journalism. Our curriculum teaches students how to interpret and explain science to the wider public, to place research and researchers within their social and historical contexts, and to create pieces that balance hard analysis with creativity and style.

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MIT’s Master of Applied Science in Data, Economics, and Design of Policy program adds a public policy track.

More resources

Learn more about MIT graduate studies at the Office of Graduate Education .

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