This IKZ Berlin and FAIRmat joint winter school invites internationally renowned lecturers to introduce machine learning in materials science and crystal growth for any scientist new to the field. There will be four main sessions:
1. Introduction to ML/AI
2. Data Mining & ML assisted experimenting
3. ML with small data
4. New potentials enabled by ML

The lectures are accompanied by a hands-on tutorial based on the NOMAD AI toolkit.

The FAIRmat team has recently extended the NOMAD infrastructure to support trajectories and workflows, including classical molecular dynamics simulations. This interactive tutorial will walk users through the new features, demonstrating how to upload data, assess the system composition and equilibration, explore the trajectory metadata, and extract archive entries to perform detailed analyses.

This WE-Heraeus-Seminar will bring together researchers at all career stages from experiment, theory, and computer science to discuss digitalization strategies for materials research. The seminar will put a main - but not exclusive - focus on two novel classes of materials: „high entropy alloys” (HEA) and „metal organic frameworks“ (MOFs).

Applications are open until March 12, 2023 on the WE-Heraeus Foundation website.

The aim of this program is to bring together a diverse scientific audience, both between scientific fields (physical sciences, materials sciences, biophysics, etc) and within mathematics (mathematical modeling, numerical analysis, statistics and data analysis, etc), to make progress on key questions of materials informatics. Applications received by January 1, 2023 will be given first priority for consideration.