Master’s of Science in Engineering in Scientific Computing



The MSE in Scientific Computing (SCMP) program at Penn provides multifaceted education in the fundamentals and applications of computational science. This education program provides a rigorous computational foundation for applications to a broad range of scientific disciplines. An education in SCMP combines a comprehensive set of core courses centered on numerical methods, algorithm development for high performance computational platforms, and the analysis of large data, and offers flexibility to specialize in different computational science application areas. Students may elect to pursue a thesis in computationally-oriented research within the School of Engineering and Applied Science.

We welcome applications from candidates who have a strong background in physical or theoretical sciences, engineering, math, or computer science. Some experience with computer programming is also strongly recommended.


Program of Study

The ten course units for the Scientific Computing degree are divided into three categories:

  1. Foundation Courses (two course units)
    • Programming Languages & Techniques (CIT 590) or Introduction to  Software Development (CIT 591), and
    • Algorithms & Computation (CIT 596)
  2. Core Requirements (three course units)
    • Math: Numerical Methods and Modeling (ENM 502) and
    • Big Data Analytics (CIS 545), and
    • Mining and Learning: Intro to Machine Learning (CIS 519) or Machine Learning (CIS 520) or Modern Data Mining (STAT 571), or Data-driven Modeling and Probabilistic Scientific Computing (ENM 531), or Data Mining: Learning from Massive Datasets (ESE 545)
  3. Technical & Depth Area Electives (five course units).
    • Two courses in which the primary focus is simulation methods for natural science/engineering. Examples include: CBE 525, CBE 544, MEAM 527, MEAM 646, MSE 561, BE 599, BE 567. Program Director approval required
    • AND
    • Two courses either Thesis/Independent study or Applications in Natural Science/Engineering
    • AND
    • One free elective (subject to approval)
Learn more about Technical and Depth Area Electives

Advanced Registration Information Slides


SCMP Administration:

If you have any questions regarding SCMP, please email Katie Thompson at kathom@seas.upenn.edu.

Helpful Links

A comparison between Scientific Computing and Data Science