This course provides an introduction to the modeling of matter at the atomic scale, using interactive jupyter notebooks to see several of the core concepts of materials science in action.
This course presents an introduction to statistical mechanics geared towards materials scientists. The concepts of macroscopic thermodynamics will be related to a microscopic picture and a statistical interpretation. Lectures and exercises will be complemented with hands-on simulation projects.
The course gives an overview of atomistic simulation methods, combining theoretical lectures and hands-on sessions. It covers the basics (molecular dynamics and monte carlo sampling) and also more advanced topics (accelerated sampling of rare events, and non-linear dimensionality reduction).
This course is designed to cover a series of important scientific aspects related to the field of additive manufacturing of metals and alloys and to provide an in-depth review of corresponding fundamentals. It features 9 modules consisting of presentations given by lecturers and the participants.
This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting
knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific