Master of Science in Computational Science and Engineering

Computational Science and Engineering

Core Subjects36
Select three of the following subjects:
Introduction to Modeling and Simulation
Optimization Methods
Numerical Methods for Partial Differential Equations
Introduction to Numerical Methods
Restricted Electives 124
Choose 24 units of coursework from the list below.
Unrestricted Elective 112
Choose any graduate-level subject. 2
CSE.THGGraduate Thesis36
Total Units108

Subjects that can be repeated for credit cannot be used to satisfy multiple CSE SM requirements.


See list of subjects offered at MIT.

Restricted Electives

1.125Architecting and Engineering Software Systems12
1.545Atomistic Modeling and Simulation of Materials and Structures12
1.583Topology Optimization of Structures12
1.723Computational Methods for Flow in Porous Media12
2.098Introduction to Finite Element Methods12
2.156Artificial Intelligence and Machine Learning for Engineering Design12
2.168Learning Machines12
2.29Numerical Fluid Mechanics12
3.320Atomistic Computer Modeling of Materials12
4.450[J]Computational Structural Design and Optimization
4.453Creative Machine Learning for Design12
6.7210[J]Introduction to Mathematical Programming12
6.7220[J]Nonlinear Optimization12
6.7230[J]Algebraic Techniques and Semidefinite Optimization12
6.7250Optimization for Machine Learning12
6.7300[J]Introduction to Modeling and Simulation12
6.7810Algorithms for Inference12
6.7830Bayesian Modeling and Inference12
6.7900Machine Learning12
6.7940Dynamic Programming and Reinforcement Learning 112
6.8300Advances in Computer Vision12
6.8410Shape Analysis12
6.C51Modeling with Machine Learning: from Algorithms to Applications 26
9.520[J]Statistical Learning Theory and Applications12
9.660Computational Cognitive Science12
10.551Systems Engineering 29
10.552Modern Control Design 29
10.554[J]Process Data Analytics12
10.557Mixed-integer and Nonconvex Optimization12
10.637[J]Computational Chemistry12
12.515Data and Models12
12.521Computational Geophysical Modeling12
12.620[J]Classical Mechanics: A Computational Approach12
12.714Computational Data Analysis12
12.805Data Analysis in Physical Oceanography12
12.850Computational Ocean Modeling12
15.070[J]Discrete Probability and Stochastic Processes12
15.077[J]Statistical Machine Learning and Data Science 112
15.083Integer Optimization 312
15.093[J]Optimization Methods12
15.764[J]The Theory of Operations Management12
16.110Flight Vehicle Aerodynamics12
16.225[J]Computational Mechanics of Materials12
16.413[J]Principles of Autonomy and Decision Making12
16.888[J]Multidisciplinary Design Optimization12
16.920[J]Numerical Methods for Partial Differential Equations12
16.930Advanced Topics in Numerical Methods for Partial Differential Equations12
16.940Numerical Methods for Stochastic Modeling and Inference12
18.335[J]Introduction to Numerical Methods12
18.336[J]Fast Methods for Partial Differential and Integral Equations12
18.337[J]Parallel Computing and Scientific Machine Learning12
18.338Eigenvalues of Random Matrices12
18.369[J]Mathematical Methods in Nanophotonics12
18.435[J]Quantum Computation12
22.15Essential Numerical Methods6
22.212Nuclear Reactor Analysis II12
22.213Nuclear Reactor Physics III12
22.315Applied Computational Fluid Dynamics and Heat Transfer12
CSE.999Experiential Learning in Computational Science and Engineering
IDS.131[J]Statistics, Computation and Applications12

Restricted elective credit can only be given for one of 6.7900, 15.077, or IDS.147.


Students cannot receive credit without simultaneous completion of a 6-unit Common Ground disciplinary module. The two subjects together count as one 12-unit restricted elective. See 6.C51 for more information.


Students receive credit for either 10.551 or 10.552 as a CSE concentration subject, but not both.


Subject to Sloan bidding process.