Open positions

The Cluster of Excellence “Machine Learning - New Perspectives for Science” at the University of Tübingen offers a position as

Research Data Steward / Data Architect (m/f/d, E13 TV-L, 100%)

The position is available in the team of the Machine Learning Science Cloud and runs until 31st December 2032.

Help us build a modern HPC architecture for training large-scale scientific research and foundation models. The Machine Learning Science Cloud is part of the AI/ML compute ecosystem in Tübingen. Our users work on diverse research and transfer projects ranging from generative climate science to large language models. This involves large, structured, and occasionally sensitive databases for training and benchmarking.

As part of a motivated team, you will work and communicate with the users and help to efficiently scale our largest machine learning experiments. You will enable an ambitious research agenda through a FAIR data strategy for the cluster’s research projects, covering the entire pipeline from project planning, data curation, data storage, building and maintaining distributed data loading pipelines, metadata description, and documentation, to archiving and subsequent use of the data. You will also interact with other entities involved in data management at the University.

What you'll do

• Develop storage strategies and data lifecycle management (hot/warm/cold).
• Design and implement data pipelines for research datasets on HPC infrastructure.
• Establish data governance policies and quality standards.
• Create and maintain dataset documentation and metadata schemas.
• Advise researchers on FAIR principles and data management plans.
• Coordinate with legal/compliance on data protection requirements.
• Work closely with users to support scalable AI experiments through stable, accessible, and high-performance data infrastructure.

What you will bring (position requirements)

• Masters degree in information technology, applied computer science or computer engineering (or comparable degree).
• Experience with data engineering.
• Familiarity with research data management and FAIR principles.
• Experience with HPC clusters.
• Experience with Linux OS (e.g. SLES/RHEL/CentOS/Ubuntu etc.).
• Experience with data pipelines/data streaming.
• Knowledge of relevant file formats (e.g. HDF5).
• Independent, result driven work, demonstrating ownership and accountability.
• Proficiency in English. German is helpful but not required.

Relevant experience in some of the following technologies

• Advanced shell scripting skills.
• Experience with Storage/Databases (SQL/object storage) and parallel file systems like GPFS/Lustre/Ceph/BeeGFS/Weka.
• Experience with automation tools for configuration management (e.g. Ansible, Puppet, Chef) and revision control systems (e.g. Git).
• Experience with containers (Docker/Singularity/Podman/Kubernetes).
• Experience with Ethernet, InfiniBand, RDMA network technologies.
• CPU/GPU/memory/RAID/storage/Data Center technologies.
• Knowledge of current technological developments/trends in area of expertise.

What you can expect

• Exciting tasks in a dedicated, international team who are fully committed to ambitious research agenda.
• Access to modern HPC systems and hardware.
• A vibrant working environment with more than 200 international researchers from all over the world.
• Family-friendly working environment.

The position should be filled as soon as possible. Applications with the usual documents should be sent via e-mail until 15th March 2026 to the Head of ML Cloud c/o. Simon Kreuzer, University of Tübingen, Maria von Linden Str 1, 72076 Tübingen, e-mail: ml-in-sciencespam prevention@uni-tuebingen.de. Hiring is done by the Central Administration of the University of Tübingen.

Severely disabled persons will be given preferential consideration if equally qualified. The University of Tübingen aims to increase the proportion of women in research and teaching and therefore invites applications from suitably qualified female candidates. The position is divisible.

Our group builds artificial intelligence systems for discovering new concepts, experiments and ideas in physics. To accelerate this effort, we need your help! We have

several fully-funded open PhD and Post-Doc positions (m/f/d)

at the University of Tübingen, one of Europe’s most vibrant hub for artificial intelligence research. 

A list of concrete potential projects:

• Development of modern auto-differentiation (JAX-based) physics simulators for the discovery of new physics experiments (example here)
• AI-driven discovery of hardware for some of the most thought after quantum information technology, quantum-enhanced microscopes and telescopes (example here), and AI-driven discovery of new physics experiments to test quantum-gravity and observe gravitational waves (examples here and here)
• Developing and testing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces motivated by physics and chemistry
• Agentic frameworks (e.g. LLMs with tool-use) for closed-loop idea generation for physics (example here)

Other projects are certainly possible too. In general, we believe that building autonomous scientific systems is not just a technical question, but requires understanding and insights from the philosophy of science – see e.g. here.

If you are excited to use artificial intelligence techniques for scientific discoveries in physics, send us your application, including a CV, a short motivation letter, the names & contact of two potential references to mario.krennspam prevention@uni-tuebingen.de. The opening will remain valid until filled.

PhD positions will be for a duration of 3 years, post-doc positions will be for 2 years.

Requirements: Master/Bachelor in Physics, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs).

The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC Starting Grant ArtDisQ and the University of Tübingen. Salary will be determined according to the German collective wage agreement in public service (E 13 TV-L). 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. 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.

View this position as PDF

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 machine learning based data analysis of scattering and diffraction data. Currently we 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 as well as in a team. You should hold either a diploma/master 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. We offer 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 Tübingen. You will receive excellent training and for all our projects we offer the opportunity to perform research at international large-scale facilities (such as synchrotrons and neutron sources).  Details on our research as well as publications and background information can be found at http://www.soft-matter.uni-tuebingen.de/machine_learning_XRR.html and http://www.soft-matter.uni-tuebingen.de/machine_learning_GIWAXS.html

The University of Tübingen has ~ 28,000 students and more than 500 years of academic tradition. It has national excellence status as is ranked 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 softmatterspam prevention@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.