Open positions

The Chair of International Economics and European Integration at the Faculty of Economics and Social Sciences at Tübingen University invites applications for the position of

1 Student Research Assistant (m/f/d)

Intended starting date is 1 June 2026. The contract will be limited to 6 months, but an extension may be possible. Working hours are negotiable between 24 – 34 hours per month and can be flexible during exam periods.

Your Responsibilities

As a student research assistant, you will support ongoing research projects on the economic effects of artificial intelligence. Your work will apply Natural Language Processing and include exploring and implementing vector embeddings for representing and matching textual data. You will also gain hands-on experience with generative AI approaches and contribute to their application in economic research settings. In addition, you will help evaluate and compare methods for text similarity and text matching, supporting the assessment and improvement of existing models.

Your Profile

You are currently enrolled as a Master’s student in a data science–related field or a comparable discipline. You have practical experience with Python and are familiar with fundamental methodologies in Natural Language Processing (NLP).

Desirable Qualifications

Ideally, you have prior experience working with natural language processing and machine learning techniques. An interest in, or basic knowledge of, economics is considered an advantage and will help you engage with the application context of the project. Disabled persons will be preferred in case of equal qualification.

How to apply

Please submit your application, preferably in electronic form, with the usual documents (CV; copies of undergraduate degree) by 1 May 2026 to mark.hellstenspam prevention@uni-tuebingen.de. In case you have questions about the position, please contact Dr. Mark Hellsten.

The Cluster of Excellence “Machine Learning – New Perspectives for Science” at the University of Tübingen is seeking a

Scientific Director (m/w/d, E14 TV-L, 100%) of the AI Methods Software Hub

The position is permanent and can be filled as soon as possible. 

The AI Methods and Software Hub for “Machine Learning in the Sciences” acts as a central interface between the Cluster of Excellence and the university's departments. It pools expertise in applied machine learning and the development and long-term use of research software. The scientific director will establish a project-based consulting structure to facilitate knowledge transfer from the Cluster of Excellence to other departments at the university and foster collaborations between machine learning and application domains. Furthermore, the director will establish structures that enable broader adoption of software packages. These software packages should be maintained long-term to ensure they are easily usable by the broader AI and machine learning community beyond Tübingen.

The director's responsibilities include:

Project consulting:

• Machine learning consulting for scientific projects from a range of disciplines.
• Development of prototypes for standard use cases.
• Organization of networking events between the ML department and scientific application subjects. 

Research software infrastructure:

• Selection of software packages for maintenance.
• Licensing for open-source projects.
• Dissemination on appropriate platforms such as github.

Leadership and Training:  

• Personnel responsibility for the AI Methods and Software Hub.
• Development of courses for introducing doctoral students and scientists from other disciplines to machine learning. Teaching in bachelor's or master's programs and transfer to industry is explicitly not required. 

We are looking for candidates with experience supporting scientific projects at the interface of machine learning and other scientific disciplines, and with expertise in structuring and maintaining research software.

The position offers options for creative developments in a vibrant environment. You will have the opportunity to contribute to publications and third-party funding applications, although this is not the primary goal of the position.

What you will bring (position requirements):

• A PhD in machine learning or data science and a background in computer science, physics, mathematics, or related subjects.
• In-depth knowledge of scientific software development.
• Good communication skills.
• Programming experience in common scientific programming languages (Python, Julia, R, C++, etc.).
• Experience in project management.
• Curiosity about research in different scientific fields, and openness to familiarize yourself with new application domains.

Further information on the Cluster of Excellence can be found at http://www.ml-in-science.uni-tuebingen.de/. Applications with the usual documents (motivation letter, CV, working experiences) should be submitted in electronic form (as a single PDF file no larger than 5 MB) by 30 April 2026 to the central office of the Cluster of Excellence (ml-in-sciencespam prevention@uni-tuebingen.de). Please also direct any questions regarding this advertisement to the central office. 

The University of Tübingen is committed to the goals of equality and diversity and actively promotes equal opportunities. Severely disabled applicants with equal qualifications and abilities will be given preferential consideration. Recruitment is carried out by the Central Administration of the University of Tübingen.
 

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