Postdoc (m,f,x) in Machine Learning Potentials, Theoretical Chemistry II, Research Alliance Ruhr
Ruhr-Universität Bochum
Germany
Summary
Three-year full-time role developing machine-learning interatomic potentials for heterogeneous catalysis and solid–liquid interfaces, implementing algorithms in scientific software, generating DFT training data, and leveraging HPC for large-scale atomistic simulations.
