Time and Place
Every Winter & Summer Semester
Lecture: 13.04 - 18:05, 9:00 - 12:30 in 5501.02.133
Project Consultation: 01.06 - 13.07, 9:00 - 11:00 in 5501.02.133
What's this course about?
In this course, you'll explore how atomistic interactions in materials determine properties such as thermal and mechanical stability. Using molecular dynamics simulations, you'll connect these microscopic interactions to the macroscopic behavior of materials. You'll also learn to apply state-of-the-art machine learning techniques to improve the accuracy of your models. By extending existing workflows for developing, testing, and applying atomistic models, you'll gain valuable hands-on experience. The lecture phase will cover the following topics:
(1) Introduction to Molecular Dynamics
(2) Connecting Molecular Dynamics to Thermodynamics
(3) Advanced Molecular Dynamics Simulations
(4) Introduction to Machine Learning
(5) Introduction to Deep Learning
(6) Machine Learning for Molecular Simulations
Learn the basics
In each weekly session during the lecture phase, the TA introduces a new topic with slides. Key concepts are discussed and illustrated using examples. The lectures gradually build upon each other.
Learn by doing
After each session, you will apply the theory to a simple problem. We will provide Jupyter notebooks that guide you step by step to the solution. The notebooks will be in Numpy and JAX.
Project Report
Summarize your approach and the project's outcome in a project report, and document your code.
The project report and documented code will determine your final grade.
