Overview
All Ph.D. students in CBE at Princeton must take a minimum of 10 courses, four of which are electives. Here, I outline a very incomplete list of potential courses that are relevant to our research and that you may wish to consider. Please feel free to add more or remove some, as this will quickly become out of date!
Fall Courses
Computational
CBE 512: Machine Learning in Chemical Science and Engineering
APC 524/MAE 506/ASR 506: Software Engineering for Scientific Computing
CBE 422/MSE 422: Molecular Modeling Methods
Materials
MSE 501: Introduction to Materials
MSE 503: Solid State Materials
Spring Courses
Computational
COS 485: Neural Networks: Theory and Applications
MSE 504/CHM 560/PHY 512/CBE 520: Monte Carlo and Molecular Dynamics Simulation in Statistical Physics & Materials Science