Stellenausschreibungen

The African Institute for Mathematical Sciences (AIMS) and the Cluster of Excellence "Machine Learning - New Perspectives for Science" at the University of Tübingen / Germany invite applications for the 

AIMS - Tübingen Junior Research Chair in Machine Learning for Science

The successful candidate will be based at AIMS Research and Innovation Centre (AIMS RIC) in Kigali, Rwanda, but will also be integrated into the Cluster of Excellence “Machine Learning – New Perspectives for Science” at the University of Tübingen, Germany. AIMS RIC is the sixth centre of the African Institute for Mathematical Sciences (AIMS), a pan-African network of Centres of Excellence for post-graduate training, research and public engagement in mathematical sciences. The network's six Centres are in South Africa (1), Senegal (1), Ghana (1), Cameroon (1), and Rwanda (2).

The AIMS - Tübingen Junior Research Chair in Machine Learning for Science is designed to strengthen mathematical higher education and research in Africa, promote networking between AIMS and German higher education institutions, in particular the University of Tübingen, and support networking amongst the various AIMS centres in Africa. The position is made possible through the partnership between the University of Tübingen and AIMS and the Excellence Strategy of Germany funded via the German Research Foundation (DFG).

Responsibilities of the AIMS - Tübingen Junior Research Chair in Machine Learning for Science

We are looking for aspiring scientists with a PhD to work on machine learning for science in a wide sense: either pursuing research on core machine learning or applying machine learning to a scientific discipline of your choice, be it in the natural sciences, social sciences, or life sciences. Specifically, a scientist who can:

• Develop and lead an exciting, high-quality program of research
• Supervise junior scientists including Postdoctoral Fellows, PhD Students, and Master students
• Contribute to the development and delivery of courses at AIMS Centres
• Host scientific events, including international conferences
• Publicly disseminate research results through high-quality peer-reviewed publications
• Disseminate research results through other media, for example, seminars, workshops, and colloquia
• Provide support to AIMS’ scientific development efforts as may be requested from time to time
• Strengthen the scientific links between the University of Tübingen and AIMS through fostering joint research projects and trainee co-supervision. In particular, the chair is expected to visit Tübingen on a regular basis.

What we offer

• The position provides competitive salary and administrative support, as well as financial support to attend and organize scientific events, to hire a postdoctoral fellow and PhD students and to cover other expenses related to leading a research group at AIMS.
• The appointment will be for a period of 6 years with the possibility of extension, subject to performance and funding availability.
• The incumbent may be promoted to a (senior) Research Chair after 3 years, subject to performance.
• Participation in the Cluster of Excellence “Machine Learning – New Perspectives for Science” at the University of Tübingen, Germany.
• Mentorship for the AIMS - Tübingen Junior Research Chair in Machine Learning for Science

Eligibility

We welcome applications from talented scientists with the following background:

• Received a PhD in machine learning, mathematics, computer science, physics, or related fields from an internationally recognized program not more than five years before appointment date
• Research expertise in Machine Learning for science.
• Strong publication record in international, peer-reviewed journals and tier-1 conferences
• Evidence of academic maturity and independence in planning research activities
• Interest in capacity development of young African scientists
• Ability to bridge theory and applications and an interest in interdisciplinary collaborations.
• Has an exciting and innovative research plan with original ideas

How to apply

To apply, please visit here by 31st August 2025, 23:59 CAT. Please prepare the following documents before starting your application:

1. Motivation letter,
2. Research statement (about 4 pages including references, outlining past research results, future research plans, and required research infrastructure),
3. CV including three referees (their names, email addresses, phone number) and details about the candidate’s PhD and a publication list. Referees will be contacted (within seven days after the deadline of this call) to send confidential letters of support on your behalf.

When filling in the online application form, please observe the guidelines for completing the application and the information on required documents. For further information and advice important for your application, you can contact applicationsspam prevention@aimsric.org and make sure your Email Subject Title is Inquiry About Application for AIMS - Tübingen Junior Research Chair in Machine Learning for Science.

*** Female candidates are strongly encouraged to apply.

Summary of the selection process

An independent Selection Committee that includes representatives of AIMS and The University of Tübingen will select the appointee to the Junior Research Chair based on an independent peer review. In a pre-selection process, suitable candidates will be determined who will be invited to Rwanda to present their work. Applicants will receive feedback immediately after the Selection Committee has made its choice.

Shortened PDF Version

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)

in our group -- which just moved from the Max Planck Institute in Erlangen to 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)
• Inventing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces motivated by physics
  and chemistry
• Developing interpretable AI for scientific discovery in physics (example here)
• Formal mathematics (using Lean’s mathlib) for Automated Discovery in Physics
• 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 explanation of your motivation, the names and contact of two potential references to mario.krennspam prevention@mpl.mpg.de. The opening will remain valid until the position is filled.

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.