Prof. Dr. Gianaurelio Cuniberti
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Innovative materials are one of the key technologies for keeping products and industrial processes economically competitive and ecologically sustainable. Modern materials science requires a multi-discipline approach embracing chemistry, physics, engineering, as well as data science. This summer school will provide an overview of current developments in data-driven materials science involving Machine Learning and modern numerical techniques and will offer a platform for discussions about future perspectives. A particular focus is put on solid state and materials mechanics and respective approaches for modelling, simulations and analysis across scales.

The summer school targets Master students, Ph.D. students and (early-stage) Postdocs interested in or working on topics related to computational mechanics, machine learning and data-driven materials science. For excellent students, up to 10 all-inclusive grants (travel support, accommodation, participation) will be available.