Open positions

Currently there are several positions to be filled.

PhD position in Complexity Reduction, Explainability and Interpretability (KEI) (m/f/d; E13 TV-L, 73%)

We invite applications for a 3-year PhD or Postdoctoral position in Philosophy of AI at the University of Tübingen, Germany, to work on the project

Complexity Reduction, Explainability and Interpretability (KEI)

 (m/f/d; E13 TV-L, 73%, 36 mo., ideal start: 01.04.2024)

funded by the Heidelberg Academy of Sciences and Humanities (HAdW).

The position is limited to 3 years. The project was elected as part of the College’s 9th season entitled “Complexity Reduction: Principles, Methods and Challenges” and is thereby part of an interdisciplinary consortium with other funded projects.

The office of the successful candidate is intended to be at the AI building in Tübingen, within the Ethics and Philosophy Lab of the Cluster of Excellence Machine Learning for Science (ML Cluster), in the direct vicinity of several renowned institutions, including the Tübingen AI Center and Max-Planck-Institute for Intelligent Systems.

The project is also in collaboration with the SimTech Cluster of Excellence "Data-Integrated Simulation Science" at the University of Stuttgart through Dr. Klopotek, head of the group Many-Body Simulations and Machine Learning. It will thus also be associated with the Stuttgart Research Focus: Interchange Forum for Reflecting on Intelligent Systems.


  • The elected applicant will be supervised by and work with PD Dr. Eric Raidl
  • The contract will lie formally at the HAdW
  • The position shall be embedded in the Ethics and Philosophy Lab, and affiliated with the ML Cluster
  • The elected applicant will also work in close exchange with the physics part of the KEI-project, directed by Dr. Miriam Klopotek (University of Stuttgart, SimTech)
  • Travel budget
  • Costs for a laptop are covered


  • Research and publication in Philosophy of AI in close collaboration with PD Dr. Eric Raidl
  • Support of PD Dr. Eric Raidl in research- and project- related tasks (communication, workshop organization, WIN-Kolleg meetings, etc)
  • Teaching is not mandatory but possible

Profile Requirements for the PhD Position

  • Excellent Master in philosophy, logic, or physics (or both)
  • Strong background in philosophy of science, philosophy of AI, epistemology, or physics
  • Knowledge of the topics of Explainable AI and Complexity (e.g., computational and algorithmic complexity, statistical physics)
  • Proficiency in English and German
  • Excellent organizational and communication skills
  • Experience in interdisciplinary discussion with scientists
  • Personal responsibility and ability to cooperate

Profile Requirements for the Postdoc Position

  • Excellent PhD in philosophy of AI, or philosophy of science, or philosophy of physics, or in logic
  • Two publications (published or accepted)
  • And the above-mentioned Profile Requirements for the PhD Position.

Please apply with the following documents –  cover letter, CV (maximally 2p each), copies of certificates, list of publications, and 1 written work for the PhD and 1 publication for the Postdoc Position  – as a single PDF; not exceeding 5 MB, to aitespam and in cc eric.raidlspam by February 15, 2024. In your cover letter, specify how your work and competences fit into the project. Incomplete applications will not be considered. Questions should be directed to eric.raidlspam Interviews are planned for the end of February.

The HAdW and the university seek to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference.

Several 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 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 and

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

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

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.