Applications are now closed. Please apply through our online application next year.
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 strongly recommended.
Interested in career prospects following a master’s degree from Penn Engineering? Please check out the attached report from 2022.
Program of Study
10 course units are required for the MSE in Scientific Computing.
- All Simulations count as Applications, all Applications count as Free Electives (cannot go backwards).
- Students cannot use Machine Learning courses to count toward the Simulations requirement. Please consult with your advisor prior to registering for courses each semester.
**If you enrolled in SCMP prior to Fall of 2023, your program of study may look slightly different. Please adhere to the old program of study found here. If you have questions about this, email Julia at jnespos@seas.upenn.edu.
Computational Mathematics (2 C.U.)
ENM 5020 (1 C.U.) and 1 C.U. of the following:
Machine Learning and Data Science (3 C.U.)
CIS 5450 (1 C.U.) and 2 C.U. of the following:
- CIS 5190: Applied Machine Learning
- CIS 5200: Machine Learning
- CIS 5220: Deep Learning for Data Science
- CIS 6200: Advanced Topics in Machine Learning
- CIS 6250: Theory of Machine Learning
- ENM 5310: Data-driven Modeling and Probabilistic Scientific Computing
- ESE 5450: Data Mining: Learning from Massive Datasets
- ESE 5460: Principles of Deep Learning
- ESE 6500: Learning in Robotics
- MSE 5760: Machine Learning and Its Applications in Materials Science
- STAT 5710: Modern Data Mining
Methods and Simulations (2 C.U.)
2 C.U. of the following:
Bioengineering (BE)
Chemical and Biomolecular Engineering (CBE)
Computer and Information Science (CIS)
Engineering Mathematics (ENM)
- ENM 5310: Data-driven Modeling and Probabilistic Scientific Computing
Electrical and Systems Engineering (ESE)
Mechanical Engineering and Applied Mechanics (MEAM)
Materials Science and Engineering (MSE)
- MSE 5610: Atomic Modeling in Materials Science
Scientific Computing Master’s Program (SCMP)
- SCMP 5590: Multiscale Modeling of Chemical and Biological Systems
Applications in Natural Science (2 C.U.)
*All simulations courses also count toward the applications requirement.
SCMP 5970: Master’s Thesis Research (2 C.U.)
SCMP 5990: Master’s Independent Study (up to 2 C.U.)**
**If you only take 1 C.U., you will need to take 1 C.U. of one of the below courses to fulfill this requirement.
or 2 C.U. of the following:
Bioengineering (BE)
Biology (BIOL)
Biomedical Informatics (BMIN)
Chemical and Biomolecular Engineering (CBE)
Computer and Information Science (CIS)
Electrical and Systems Engineering (ESE)
- ESE 5230: Quantum Engineering
Mechanical Engineering and Applied Mechanics (MEAM)
- MEAM 5040: Tribology
- MEAM 5060: Failure Analysis of Engineering Materials
- MEAM 5070: Fundamentals of Materials
- MEAM 5080: Materials and Manufacturing for Mechanical Design
- MEAM 5100: Design of Mechatronic Systems
- MEAM 5200: Introduction to Robotics
- MEAM 5380: Turbulence
- MEAM 5430: Performance, Stability and Control of UAVs
- MEAM 5450: Aerodynamics
- MEAM 5700: Transport Processes I
- MEAM 5800: Electrochemistry for Energy, Nanofabrication and Sensing
- MEAM 6200: Advanced Robotics
- MEAM 6420: Advanced Fluid Mechanics
- MEAM 6900: Advanced Topics in Thermal Fluid Science or Energy
Materials Science and Engineering (MSE)
Physics (PHYS)
- PHYS 5517: Particle Cosmology
Free Elective (1 C.U.)
Any technical course, subject to advisor approval.