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 on-campus information session for prospective students on Friday, November 3, 2017.  Watch the video of the program overview presentation here.
(NOTE: the CSE degree requirements have changed slightly since the Information Session on November 3.  Please see the DEGREE REQUIREMENTS section below for updates.)

Admissions

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.  Applications to the Master of Science in CSE program are now being accepted for entry into the program in Fall 2018.  Apply Here.

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. 

Learning Outcomes

The design of the program is based on ten 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.

The CSE faculty committee met on November 10, 2017 and approved some modifications to the degree requirements.  These modifications will take effect for students entering the program in fall 2018 and are highlighted below.

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

  • AM 205: Numerical Methods (UPDATED CHANGE)
  • at least two of the three core courses(UPDATED CHANGE)
  • at least one research experience.  This requirement can be satisfied by the AC 297r Capstone project course or a semester-length independent study project.  (UPDATED CHANGE)
  • 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 of the AC 298r seminar course.
  • as a final requirement, an oral examination by a faculty committee. 

SM course requirements at a glance:

SM Course Requirements at a Glance
SM Requirements Number Required
AM 205: Numerical Methods 1
Additional Core Courses: CS 025, AM 207, CS 207 2
Research Experience (AC 297r or AC 299r) 1
Applied Math elective 1
Computer Science elective 1

Additional courses:

Applied Math electives (up to 2)
Computer Science electives (up to 2)
Domain electives (up to 2)
Research course (up to 1)
AC 298r Seminar course (up to 1)

2
TOTAL 8