PhD Position: Machine Learning for Analysis of Scattering Data

The Institute of Applied Physics at Universität Tübingen invites applications for a PhD position within the research group led by Prof. Dr. Dr. h.c. Frank Schreiber. The successful candidate will focus on creating innovative machine learning strategies to efficiently analyze large datasets generated from molecular and biological scattering experiments. Working within an international team, the researcher will develop software tools for surface-sensitive techniques like X-ray Reflectivity and Grazing-Incidence Wide-Angle X-ray Scattering. Applicants are expected to contribute to top-level scientific experiments, integrate software into computational environments, and present results at conferences and in publications.

• Develop machine learning-based tools to analyze data from surface-sensitive scattering techniques including X-ray Reflectivity and Grazing-Incidence Wide-Angle X-ray Scattering
• Contribute to scattering data analysis and support data and metadata formats developed within the research group
• Integrate developed software into existing computational environments and data handling routines
• Present scientific findings at international conferences and through academic publications