PhD position: machine learning for analysis of scattering data

About this position

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 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.

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

Applications should be accompanied by a cover letter describing motivation, skills and any special achievements. Furthermore, a CV and a transcript of records should be added. The position is to be filled immediately. Please send your application in one PDF file to softmatter@ifap.uni-tuebingen.de