Stellenausschreibungen

Die Arbeitsgruppen Methods of Machine Learning und Machine Learning in Science des Fachbereichs Informatik am Tübingen AI Center erforschen Methoden des maschinellen Lernens und deren Anwendungen in den Wissenschaften. Für unsere Teams suchen wir zum 1. März 2026

zwei Verwaltungsangestellte (w/m/d, E9a TV-L, je 50%)

Der/die Stelleninhaber/innen unterstützen uns in verwaltungs- und finanztechnischen Aufgaben. Diese umfassen insbesondere

• Eigenverantwortliches Finanz- und Personalmanagement der Arbeitsgruppen (inkl. Abruf, Verwaltung und Dokumentation umfangreicher Drittmittel aus verschiedenen Quellen mit unterschiedlichen Reporting- und Controlling- Vorgaben)
• Beschaffung und Verwaltung von Sachgütern für die Forschung; Verwaltung von Dienstreisen; Organisation und Abwicklung von Reisekosten.
• Organisatorische Verantwortung für die Planung und Durchführung von Workshops, Symposia, Tagungen und internen Veranstaltungen.
• Allgemeine Verwaltungs- und Sekretariatsaufgaben.

Gesucht werden eine oder zwei Personen mit abgeschlossener kaufmännischer Ausbildung oder einem vergleichbaren Berufsabschluss. Quantitative Fähigkeiten sowie Erfahrungen im Universitäts- und Wissenschaftsmanagement oder in der öffentlichen Finanzverwaltung, sind wünschenswert. Sehr gute Englischkenntnisse sind unabdingbar (große Teile des Arbeitsalltags finden in englischer Sprache statt). Erfahrung mit universitären Datenbanken und Prozessen ist wertvoll, genauso wie gute Kommunikationsfähigkeiten im Umgang mit KollegInnen, Studierenden, Gästen und der Öffentlichkeit in einem international geprägten Umfeld. 

Die Arbeitszeiten können in gemeinsamer Abstimmung flexibel, verbindlich, und familienfreundlich gestaltet werden.

Die Universität Tübingen setzt sich für die Ziele der Gleichstellung und Diversität ein, und fördert aktiv Chancengleichheit. Schwerbehinderte werden bei gleicher Eignung bevorzugt eingestellt.

Bitte senden Sie Ihre vollständigen Bewerbungsunterlagen in einem PDF-Dokument bis zum 16. Januar 2026 an mmlsspam prevention@inf.uni-tuebingen.de

The Chair for Machine Learning in Science (Prof. Dr. Jakob Macke) at the Excellence Cluster “Machine Learning: New Perspectives for Science” at the University of Tübingen has an opening for

Research Engineer (m/f/d) (E13 TV-L)

working at the intersection of

Machine Learning and Computational Neuroscience

We are building large-scale biologically inspired neural networks simulating information processing in the fruit fly visual system (Lappalainen et al., Nature, 2024), funded by the ERC Grant DeepCoMechTome. You will play a key role in these efforts by

(1) developing and maintaining high quality research code and open-source packages,
(2) training large-scale mechanistic neural networks on GPU clusters, and
(3) designing and implementing new features at the cutting edge of scalable mechanistic modeling.

Your work will involve efficient implementation of differentiable simulators for neural activity (https://github.com/jaxleyverse/jaxley), maintaining and advancing methods for simulation-based inference (https://github.com/sbi-dev/sbi) and collaborative development of large-scale neural simulations (https://github.com/TuragaLab/flyvis).

Candidate qualifications:

We are looking for a candidate who is driven by improving research code quality, accessibility and reproducibility. Together, we are stepping into a new era of scaling biologically realistic neural modeling. We are looking for someone who is excellent at problem-solving, has a strong quantitative background (ideally, Engineering/Math/CS), and is passionate about their work. An ideal candidate has a post-graduate degree in a relevant discipline, including but not limited to machine learning, computational neuroscience, and/or numerical simulation. If you are genuinely interested in
collaborative work at the frontier of AI and computational neuroscience, come and work with us!

Application:

Initial fixed-term contracts will be until 30th June 2028 with possible extension; starting date is flexible. Employment will be carried out by the central administration of the University of Tübingen. Please submit your application materials to mls-jobsspam prevention@inf.uni-tuebingen.de, including a CV with publication list, relevant transcripts, a statement of motivation, contact details of two referees (all in a single pdf), and a link to a code repository (or work samples). Please apply before January 10, 2026.

Our group and campus:

We (www.mackelab.org) develop machine learning and AI methods to accelerate scientific discovery, with a particular focus on neuroscience. We aim to provide an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. Working language in the group and institute is English (and many academics in Tübingen do not speak German). We are embedded in Tübingen’s renowned community in AI and computational neuroscience, including the Tübingen AI Center, the ELLIS Institute, the Excellence Cluster Machine Learning, the Bernstein Center for Computational Neuroscience, and Hertie AI. We are located in the new Cyber Valley Research Building, in a collaborative space shared with groups from the AI Center and ELLIS. 

Institutional commitment to diversity, equity, and inclusion:

The university is committed to equal opportunities and diversity and seeks to raise the number of women in research and teaching. We urge qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference in the hiring process.

An der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Tübingen ist im Fachbereich Physik eine

W3-Professur für
Maschinelles Lernen und Physik (m/w/d)

zum nächstmöglichen Zeitpunkt zu besetzen.

Die Professur ist eingebettet in den Exzellenzcluster „Maschinelles Lernen: Neue Perspektiven für die Wissenschaft“, der nun in die zweite Förderperiode geht. Von der Stelleninhaberin/dem Stelleninhaber wird erwartet, dass er/sie ein ausgewiesenes Forschungsprofil in einem Kerngebiet der Physik hat, und gleichzeitig ein ausgewiesenes Profil zu Forschungsfragen aus dem Umfeld des Maschinellen Lernens bzw. der Künstlichen Intelligenz. Kerngebiete der Physik liegen in der Struktur kondensierter Materie (Beschreibung von Vielteilchensystemen), der Quantenphysik (Charakterisierung von Quantenzuständen in Vielteilchensystemen) sowie der theoretischen Teilchenphysik. In allen diesen Bereichen findet Methodenentwicklung durch Maschinelles Lernen statt, z.B. bei der Vorhersage der Entwicklung komplexer molekularer Systeme über längere Zeitskalen, der Untersuchung quantenmechanischer Effekte in der Informationsverarbeitung innerhalb (Quanten-)Neuronaler Netzwerke oder der Physik von Elementarteilchen an Hochenergiebeschleunigern.  

Ziel der Professur ist, in Synergie mit bestehenden Aktivitäten die Forschung in einem der Forschungszentren des Fachbereichs Physik (BioNanoPysics Center, Center for Quantum Science oder Kepler Center) eng mit der Forschung im Bereich des maschinellen Lernens in Tübingen zu verbinden. Es wird erwartet, dass die Stelleninhaberin/der Stelleninhaber sich aktiv im Fachbereich Physik einbringt und am Exzellenzcluster beteiligt. Das umfasst einerseits die Bereitschaft, gemeinsame Forschungsprojekte an der Schnittstelle zwischen dem maschinellen Lernen und der Physik durchzuführen, anderseits auch die Bereitschaft, an den anfallenden Aufgaben im Bereich der Organisation und Umsetzung des Exzellenzclusters mitzuwirken. Weitere Informationen zum Exzellenzcluster finden Sie auch unter http://www.ml-in-science.uni-tuebingen.de/ 

In der Lehre wird erwartet, dass die Professur Lehrveranstaltungen am Fachbereich Physik anbietet und sich auch im internationalen Master-Studiengang „Machine Learning“ des Fachbereiches Informatik einbringt.

Einstellungsvoraussetzung ist eine Habilitation einschlägiger Ausrichtung oder eine gleichwertige Qualifikation und international beachtete Publikationen in einem der oben genannten Forschungsbereiche sowie nachgewiesene didaktische Eignung. Erfahrung in der Drittmitteleinwerbung ist erwünscht.

Die Universität Tübingen setzt sich für die Ziele der Gleichstellung und Diversität ein und fördert aktiv Chancengleichheit. Zur Erhöhung des Anteils von Frauen in Forschung und Lehre bitten wir qualifizierte Wissenschaftlerinnen nachdrücklich um ihre Bewerbung. Qualifizierte internationale Wissenschaftlerinnen und Wissenschaftler sind ausdrücklich aufgefordert, sich zu bewerben. Schwerbehinderte Menschen werden bei gleicher Eignung bevorzugt berücksichtigt.

Bitte reichen Sie Ihre Bewerbungsunterlagen über das Bewerbungsportal der Universität Tübingen unter https://berufungen.uni-tuebingen.de bis zum 15.2.2026 ein. Rückfragen zur Ausschreibung und Fragen zum Bewerbungsportal können an den Dekan der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Tübingen, Prof. Dr. Thilo Stehle (careerspam prevention@mnf.uni-tuebingen.de), gerichtet werden.

Are you excited about the possibility to explore ethical, philosophical, legal, epistemic or social implications of using machine learning in different scientific disciplines? Join us as

Postdoctoral Researcher

in anthropology, law, science and technology studies, ethics, or philosophy

for the Norms & Practices Lab (m/w/d; E13 TV-L, 100%)

in the Excellence Cluster “Machine Learning - New Perspectives for Science”

The Cluster of Excellence "Machine Learning - New Perspectives for Science" at the University of Tübingen offers several postdoc positions in our Norms & Practices Lab to be filled as soon as possible. The positions will be filled by highly qualified researchers who investigate machine learning from ethical, philosophical, anthropological or legal perspectives.

The aim of the Norms & Practices Lab of the Cluster of Excellence is to investigate from an interdisciplinary perspective how the advent of transformative machine learning and artificial intelligence technologies changes the norms and practices of science, drawing on a rich set of methodological approaches and theoretical frameworks from philosophy, digital anthropology, science and technology studies, and law. The lab places a particular emphasis on creating synergies between these disciplinary approaches and connecting them with computer science perspectives and insights. Research could for example investigate the transformation of epistemic norms and practices in scientific domains, study data journeys from the perspective of legal norms and scientific practices, or explore interdisciplinary perspectives on quantitative evaluation metrics such as algorithmic fairness paradigms. 

Applicants should hold a PhD in philosophy, law, cultural anthropology, or (qualitative) social science. The positions are fixed-term (6 years with an interim evaluation after 3 years), with a salary according to the German public sector (100%, E13 TV-L). 

Tübingen is a leading place for research in machine learning. The Research Fellows will be embedded in the lively and interactive environment of the Cluster of Excellence “Machine Learning: New Perspectives for Science” at the University of Tübingen (www.ml-in-science.uni-tuebingen.de). Also on our campus are the Tübingen AI Center, the Max Planck Institute for intelligent Systems, and the Ellis Institute.

Please send the usual documents (cover letter, curriculum vitae, copies of certificates, list of publications, 2-3 names of referees) together with a 1 page pitch on a planned research project outlining research objectives and how you want to achieve them. Please submit all documents as a single PDF (not exceeding 5 MB) to the Central Office of the Cluster of Excellence (ml-in-sciencespam prevention@uni-tuebingen.de) by November 30, 2025. Questions can also be directed to the Central Office. 

The University aims to increase the proportion of women in research and therefore urges suitably qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Disabled persons with equal aptitude will be given preferential consideration. Staffing will be conducted 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 28.10.2025 (unless filled before).

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.