PhD position: machine learning for analysis of scattering data

Universität Tübingen; Deutschland; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading research university in Germany is seeking a PhD student to join their team focusing on the application of machine learning in analyzing X-ray and neutron scattering data. The role offers a chance to work within a collaborative international research group, develop ML tools, and gain practical experience in cutting-edge scientific projects. Candidates should possess a Master’s degree in a relevant field and programming skills in Python.

Leistungen

Access to well-equipped laboratories

Highly collaborative environment

Training and supervision opportunities

Qualifikationen

• Candidates should exhibit motivation to learn and familiarize with new subject areas.
• Experience with programming languages such as Python is advantageous.
• Knowledge of German is a plus but not required.

Aufgaben

• Develop ML-based tools to analyze scattering data.
• Support data analysis and handle metadata formats.
• Integrate software into data handling routines.
• Present scientific results at conferences.

Kenntnisse

Good communication skills

Programming skills (Python)

Ability to work independently and in a team

Ausbildung

Master’s degree in physics, chemistry, or computer science

Tools

Python

PyTorch

JAX

Jobbeschreibung

Organisation/Company Universität Tübingen Department Institut für Angewandte Physik Research Field Physics » Solid state physics Physics » Condensed matter properties Chemistry » Physical chemistry Computer science » Programming Computer science » Systems design Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 28 Feb 2026 - 23:59 (Europe/Berlin) Type of Contract Temporary Job Status Full-time Hours Per Week 39.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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.

Responsibilities

• 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 [e-mail]

Where to apply

E-mail [e-mail]

Requirements

Research Field Physics Education Level Master Degree or equivalent

Research Field Chemistry Education Level Master Degree or equivalent

Research Field Computer science Education Level Master Degree or equivalent

Skills/Qualifications

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.

Specific Requirements

• Master’s 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

Languages ENGLISH Level Good

Additional Information

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

Eligibility criteria

The University seeks to raise the number of women in research and teaching and therefore emphatically calls on qualified women to apply. Disabled candidates will be given preference over other equally qualified applicants. The university is committed to equal opportunities and diversity. It therefore takes individual situations into account and asks for relevant information. The employment will be handled by the central administration of the University of Tübingen.