Job Information
- Organisation/Company
- University of Tübingen
- Department
- Institute of Applied Physics
- Research Field
- Physics » Solid state physicsPhysics » Chemical physicsPhysics » Computational physics
- Researcher Profile
- First Stage Researcher (R1)
- Country
- Germany
- Application Deadline
- Type of Contract
- Temporary
- Job Status
- Full-time
- Offer Starting Date
- Is the job funded through the EU Research Framework Programme?
- Not funded by an EU programme
- Is the Job related to staff position within a Research Infrastructure?
- No
Offer Description
The research group of Prof. Dr. Frank Schreiber at the University of Tübingen (Institute of Applied Physics) deals with the physics of molecular and biological materials using X-ray and neutron scattering and runs a specialized subgroup on machine learning (artificial intelligence and deep learning) for the analysis and prediction of experimental scattering data. Currently, there are several options for doctoral theses. Candidates interested in one of the following three areas are particularly encouraged to apply:
- X-ray photon correlation spectroscopy (XPCS) to study the dynamics of proteins and thin films on surfaces
- X-ray nano-diffraction and perovskite systems
- Neural networks and machine learning strategies for the analysis of scattering data
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, an interest in detail and motivation to familiarize themselves with new subject areas. Both working independently and working in a team, e.g. during the measurement campaigns, is particularly demanding. For the project with a focus on machine learning / AI, we also welcome applications from candidates with a focus on computational physics.
Depending on the project, the activities may include the following aspects: 1) participation in measurement campaigns at major international facilities (synchrotron and neutron sources) 2) data analysis of scattering data 3) systematic, experimental work in the laboratory 4) further development of models based on neural networks
- Languages
- ENGLISH
- Level
- Good
- Research Field
- PhysicsChemistry
Additional Information
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) for all the projects mentioned. Details of the research activities as well as publications and background information are available on the group website:
Eligibility criteria
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 positions are to be filled immediately. Please send your application in one PDF file to softmatter@ifap.uni-tuebingen.de
Additional comments
The University of Tübingen has around 28,000 students and more than 500 years of academic tradition. It has a national status of excellence and is one of the top 100 universities in the world.
Work Location(s)
- Number of offers available
- 3
- Company/Institute
- Universität Tübingen
- Country
- Germany
- City
- Tübingen
- Postal Code
- 72076 Tübingen
- Street
- Auf der Morgenstelle 10
- Geofield
Where to apply
- softmatter@ifap.uni-tuebingen.de
Contact
- City
- Tübingen
- Website
- Street
- Auf der Morgenstelle 10
- Postal Code
- 72076
- softmatter@ifap.uni-tuebingen.de