PhD student / doctoral candidate in Physics (m/f/d, E13 TV-L, 50-75%)

Stellenangebote

07.09.2026

Faculty of Science, Institute of Applied Physics

• Bewerbungsfrist : 01.12.2026
• The group “Physics of molecular and biological matter” at the University of Tübingen is searching for a

PhD student / doctoral candidate in Physics

• (m/f/d, E13 TV-L, 50-75%)
• The position is limited for three years.

Description of the project

The research group of Prof. Dr. Dr. h.c. Frank Schreiber at the University of Tübingen works on the physics of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering experiments. For more information, visit our web page www.soft-matter.uni-tuebingen.de

We are currently looking for a PhD student to join our team and help us make exciting new advances in applications of machine learning (ML) strategies for analyzing X-ray and neutron scattering data. You will apply these tools predominantly to novel optoelectronic and photovoltaic materials. You will be working in an international research group at the Institute of Applied Physics together with experienced scientists. You will contribute to the top scientific experiments, will obtain practical experience, improve your soft skills (presentation, communication, language, etc), learn the strategies of data organization and analysis.

Qualification and skills

Candidates should have good communication skills and motivation to familiarize themselves with new subject areas. The role requires both independent work and effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Participation in teaching activities (e.g., supervising practical courses or tutorials) may also be possible. While knowledge of German is not required, it will be considered a plus.

Your tasks

• Development of ML-based tools to analyse data from different surface sensitive scattering techniques (X-ray Reflectivity (XRR), Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS) and others)
• Contribution to the scattering data analysis and support of data/metadata formats developed in the group
• Integration of the developed software into the computational environments and data handling routines
• Presentation of the scientific results on conferences and in publications

Requirements

Masters degree in physics or chemistry, computer science or equivalent

Interest in Physics and Machine Learning

Good written and spoken English

• Ability to work both independently and in a team
• Programming skills (Python) and acquaintance with modern machine learning frameworks (PyTorch/JAX) are strong advantages

Benefits

The positions offered provide access to challenging and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. The group offers well-equipped laboratories, a highly collaborative international environment and membership of the Cluster of Excellence 'Machine Learning: New Perspectives for Science', which is funded by the DFG and is located at the University of Tübingen. Students in the group receive excellent training and supervision and the opportunity to conduct research at large-scale international facilities, such as synchrotron and neutron sources. Details of the research activities as well as publications and background information are available on the group website: https://www.soft-matter.uni-tuebingen.de

Additional comments

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