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. Foundations (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 (ENM531), or Data Mining: Learning from Massive Datasets (ESE 545)
  3. Technical & Depth Area Electives (five course units).
    • Students must choose two courses from Bucket B (Simulation Methods for Natural Science/Engineering)
    • AND
    • Two courses from either Bucket A (Thesis/Independent) or Bucket C (Applications in Natural Science/Engineering)
    • AND
    • One free elective (subject to approval)

SCMP BUCKETS 

Technical and Depth Area Elective (5 CU)

A. Thesis/Practicum (two course units)

Two CU of SCMP 597 or SCMP 599 

B. Simulation Methods for Natural Science/Engineering

Molecular Modeling and Simulations (CBE 525)

Computational Science of Energy and Chemical Transformations (CBE 544)

Finite Element Analysis (MEAM 527)

Computational Mechanics (MEAM 646)

Atomic Modeling in Materials Science (MSE 561)

Multiscale Modeling of Biological Systems (BE 599)

Mathematical Computation Methods for Modeling Biological Systems (BE 567)

C. Natural Science/Engineering

Any course in which the primary focus is physical/chemical/biological/mechanical application area that may be studied computationally is allowed, subject to approval

Information re: A comparison between Scientific Computing and Data Science can be accessed here

Administration:

Please visit the Penn Engineering’s Graduate Studies page for information on application materials, application deadlines, and a link to the online application.

Please visit the Graduate Student Center’s page for information on graduate student life and available resources at Penn.