The overall goal of the research is to use machine learning methods to address current problems in theoretical chemistry. At the heart of the group is the prediction of (light-induced) reactions, the design of novel materials with generative models, and the interpretation of models for the discovery of chemical rules still hidden behind the complexity of the data and ML models.


1.10.: Rhyan Barrett joined the group as a PhD student.
He will work on the development of deep learning methods. He will use reinforcement learning to discover reaction pathways in organic molecules, peptides, and proteins and to better understand their self-assembly process.

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Theoretical Chemistry of complex matter

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