Master of Science in CSE

Harvard's degree program in Computational Science and Engineering (CSE) is an intensive year of coursework leading to the Master of Science.

The one-year SM program, developed by the Institute for Applied Computational Science (IACS), provides rigorous training in the mathematical and computing foundations of CSE. Independent research projects and elective courses focusing on the application of computation to one or more domains complement the foundational coursework.

IACS hosted an Information Session for prospective students on Friday, November 4, 2016.  Please take a moment to view Daniel Weinstock's presentation on the curriculum and application process.
 

Admission

Students are admitted to the program through the Graduate School of Arts and Sciences. GSAS requires online submission of applications for graduate study. In general, applicants must hold the BA or equivalent degree. GSAS considers students for admission to the fall term only. Additional rules and requirements, including SEAS program requirements and application deadline for graduate admission, are outlined on the GSAS website.  Application information specific to the CSE program can be found here. 

Answers to questions frequently asked by both external applicants and Harvard students interested in the master's program can be found in the FAQ.

IACS welcomes inquiries from all qualified prospective students interested in exploring the emerging field of computational science. For detailed information about studying CSE at Harvard, please contact Daniel Weinstock, Associate Director of Graduate Studies in CSE.

Learning Outcomes

The design of the program is based on eight learning outcomes, developed through discussions with the IACS Advisory Board. Each student's plan of study should address these outcomes.

The outcomes answer the question: "What should a graduate of our CSE program be able to do?"

  1. Frame a real-world problem such that it can be addressed computationally
  2. Evaluate multiple computational approaches to a problem and choose the most appropriate one
  3. Produce a computational solution to a problem that can be comprehended and used by others
  4. Communicate across disciplines 
  5. Collaborate within teams 
  6. Model systems appropriately with consideration of efficiency, cost, and the available data
  7. Use computation for reproducible data analysis
  8. Leverage parallel and distributed computing
  9. Build software and computational artifacts that are robust, reliable, and maintainable
  10. Enable a breakthrough in a domain of inquiry

Degree Requirements

Requirements for the SM degree address these learning outcomes.  A total of eight courses are required.

Each student's plan of study for the SM degree will include:

  • at least three of the four core courses.
  • at least one Applied Math elective and one Computer Science elective chosen from the suggested electives list.
  • up to two “domain electives”—approved courses within a domain of study. If two domain electives are included in the plan of study at least one of them must be computation-intensive.
  • up to one semester-length independent research project.
  • up to one semester of the AC 297r capstone project course.
  • up to one semester of the AC 298r seminar course.
  • as a final requirement, an oral examination by a faculty committee. 

SM course requirements at a glance:

  SM requirements min max
1. Core 3 4
2. Applied Math electives 1 4
3. Computer Science electives 1 4
4. Domain electives 0 2
5. AC 297r capstone project course 0 1
6. AC 298r seminar 0 1
7. AC 299r independent study research course 0 1
  Total 8