Philipp Hennig

Up to 3 PhD positions are open in the interdisciplinary EXPRESSO project, part of the Tübingen Excellence Cluster Machine Learning: New Perspectives for Science at the University of Tübingen. The project focuses on quantum physics and machine learning , with research topics including probabilistic simulation and inference for quantum gases, simulation-guided model discovery via adaptive amortized inference, and representation learning for optimization in exponential search spaces. Supervision is shared across physics and machine learning by Philipp Hennig, Mario Krenn, Igor Lesanovsky, Jakob Macke, and Georg Martius. The positions are tightly integrated and designed for candidates interested in bridging quantum science, probabilistic inference, deep learning, and optimization. Applicants should have a Master’s degree in Physics, Computer Science, Mathematics, or a related field, plus strong mathematical and programming skills. Experience in quantum mechanics, Bayesian methods, or deep learning is an advantage. The team also values interdisciplinary motivation and the ability to build concrete software artifacts. Funding is a paid PhD appointment at TV-L E13, 75% for 3 years. Applications are reviewed on a rolling basis, and early applications are strongly encouraged. The review period closes on 14 September 2026. To apply, submit a CV, a short motivation letter, and the names of two referees via the application form, and indicate your preferred project(s).