PhD Student in Physics of Molecular and Biological Matter: Machine Learning for X-ray and Neutron Scattering Data Analysis University of Tübingen in Germany

The Physics of Molecular and Biological Matter group at the University of Tübingen, led by Prof. Dr. Dr. h.c. Frank Schreiber, is seeking a highly motivated PhD student to join their interdisciplinary research team. The group specializes in the study of molecular and biological matter using advanced X-ray and neutron scattering techniques, with a strong focus on developing machine learning (ML) approaches for efficient data analysis. This position offers the opportunity to contribute to cutting-edge research at the intersection of physics, chemistry, computer science, and materials science.

The successful candidate will work on the development of ML-based tools to analyze data from surface sensitive scattering techniques such as X-ray Reflectivity (XRR) and Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS). Responsibilities include supporting data and metadata formats, integrating software into computational environments, and presenting scientific results at conferences and in publications. The role involves both independent research and collaboration with experienced scientists, particularly during measurement campaigns at synchrotron and neutron facilities.

Applicants should hold a Master's degree in physics, chemistry, computer science, or a related field, and demonstrate a strong interest in physics and machine learning. Proficiency in Python and familiarity with ML frameworks like PyTorch or JAX are highly desirable. Good communication skills, motivation to learn new topics, and the ability to work both independently and in a team are essential. While German language skills are not required, they are considered an advantage.

The position is funded at the E13 TV-L, 65% level for three years and is integrated into large national and European research consortia, including the DAPHNE NFDI consortium. The group offers access to well-equipped laboratories, a collaborative international environment, and membership in the Cluster of Excellence "Machine Learning: New Perspectives for Science" funded by the DFG. Students benefit from excellent training, supervision, and opportunities to conduct research at major international facilities.

The University of Tübingen is recognized as one of Germany's Universities of Excellence, with a rich academic tradition and a vibrant student life. The university is committed to equal opportunities and diversity, encouraging applications from women and disabled candidates. The position is available immediately, with an application deadline of February 28, 2026.

For more information about the group and research activities, visit the group website. To apply, prepare a cover letter, CV, and transcript of records, and submit them as a single PDF file to the provided email address. For the official job advertisement and application details, see the university careers page.