Tristan Bereau

PhD opportunity in generative machine learning for molecular thin films at the Institute for Theoretical Physics, Heidelberg University , in the group of Prof. Tristan Bereau , with a joint collaboration with Prof. Ullrich Köthe . The project focuses on developing generative machine-learning methods for amorphous molecular thin films , which are important supramolecular structures for organic-electronic materials . The research combines statistical mechanics , molecular simulation , and deep generative modeling , with an emphasis on diffusion models , coarse-grained representations, and free-energy estimation. The successful candidate should have a strong background in statistical mechanics , experience in machine learning and/or molecular simulation , and strong Python and PyTorch skills. A genuine interest in method development and comfort with mathematical formalism are important. A physics degree is required for admission to the Heidelberg Graduate School for Physics. The position is fully funded for three years at 75% E13 TV-L . There is no application deadline ; applications are reviewed on a rolling basis until the position is filled. To apply, send a CV , a short statement of interest , and the names of two referees to bereau@thphys.uni-heidelberg.de .