PhD positions in Machine Learning Based Data Anaysis of Scattering and Diffraction Data

The Schreiber Group at the University of Tübingen works on the physics of molecular and biological materials using X-ray and neutron scattering. A specialised sub-group is dedicated to machine learning based data analysis of scattering and diffraction data. Currently, they have several PhD positions (m/f/d) available. Candidates with experience or interest in neural networks and machine learning strategies to analyse scattering are especially encouraged to apply.

You should have good communication skills, attention to detail, and flexibility to work both independently and in a team. You should hold either a diploma/master's degree in physics, physical chemistry, material science, or have a background in computer science.

You will be part of challenging interdisciplinary projects that are integrated into major national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. The Schreiber Group offers well-equipped laboratories, a highly collaborative international environment, and affiliation with the Cluster of Excellence "Machine Learning: New Perspectives for Science" funded by the DFG and hosted at the University of Tübingen. You will receive excellent training, and for all their projects, they offer the opportunity to perform research at international large-scale facilities (such as synchrotrons and neutron sources).  

Details on their research, as well as publications and background information, can be found at: 

• http://www.soft-matter.uni-tuebingen.de/machine_learning_XRR.html 
• http://www.soft-matter.uni tuebingen.de/machine_learning_GIWAXS.html

The University of Tübingen has around 28,000 students and more than 500 years of academic tradition. It has a national excellence status and ranks in the top 100 universities worldwide. You will benefit from a variety of training opportunities and language courses, as well as the university’s graduate academy.

See also https://uni-tuebingen.de/en/excellence-strategy.

Applications should include a cover letter describing research interests, achievements, motivation, and capabilities; curriculum vitae; academic certificates; names and email addresses of two professional references (e.g., current or previous research advisors). The opening will remain valid until the position is filled.

The positions are available immediately. Salary will be determined according to the German collective wage agreement in public service.

Please send your application within one PDF file to softmatter@ifap.uni-tuebingen.de 

The University aims to increase the proportion of women in research and teaching and therefore urges suitable, qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Severely disabled persons with equal aptitude will be given preferential consideration.