Open positions

The Faculty of Humanities at the University of Tübingen invites applications for the position at the Department of Philosophy of a

Tenure-Track Professor for Philosophy of Machine Learning for Science

to commence as soon as possible.

The tenure-track position is embedded in the Cluster of Excellence “Machine Learning: New Perspectives for Science”. The successful candidate has both a strong research profile in a central area of philosophy and strong connections to machine learning and artificial intelligence. Possible research fields in philosophy include practical philosophy (e.g. normative ethics, action theory or political philosophy) or theoretical philosophy (e.g. theory of science, epistemology or philosophy of mind). Examples of typical combinations of philosophy and machine learning may include practical philosophy and ethics of machine learning or artificial intelligence; theoretical philosophy and theory of science for machine learning or artificial intelligence (e.g. explanation of and trust in algorithms).

The aim of this professorship is to establish solid connections and collaborations between the Department of Philosophy and the Machine Learning community in Tübingen. It is expected that the successful candidate actively participates in the Cluster of Excellence. This includes, on the one hand, the readiness to pursue joint projects at the intersection of machine learning and philosophy and, on the other hand, to be involved in organizational tasks and the implementation of the Cluster of Excellence. Further information about the Cluster can be found here: https://uni-tuebingen.de/en/133840

In teaching, it is expected that the successful candidate offers seminars and courses at the Department of Philosophy and possibly also in the international MSc programme “Machine Learning” at the Department of Computer Science.

Prerequisites for this position comprise an excellent dissertation and a strong publication record in the research areas mentioned above. Experience in acquiring third-party research funding and in academic teaching is advantageous. The appointment prerequisites of § 51 LHG apply. Candidates who have already completed a habilitation will be excluded. Applicants for a tenure-track professorship with a PhD from Tübingen must have changed universities after completing their doctorates or have worked in academia and/or research for at least two years somewhere other than the University of Tübingen.

This position is initially limited to four years, with the possibility of an extension by a further two years in case of a positive interim evaluation. During this time, the position comes with a teaching load of four hours per week prior to the interim evaluation, and six hours thereafter. After the initial six years and a successful final evaluation, this tenure-track professorship can be upgraded to a full (W3) professorship, with no re-advertising of the position.

Detailed information on the criteria underlying the interim evaluation and promotion to the tenured position can be found in our guidelines for tenure review under the following link: https://uni-tuebingen.de/en/12131.

The University of Tübingen is committed to equity and diversity and actively promotes equal opportunities. Female academics, in particular, are explicitly invited to apply, as are applicants from outside Germany.

Applications from equally qualified candidates with disabilities will be given preference.

General information on professorships, hiring processes, and the German academic system can be found here: uni-tuebingen.de/en/213700

Applications including all required documents (cover letter, curriculum vitae, copies of degree documents/ diplomas/ certificates, list of publications and teaching experience, teaching evaluations, research and teaching statement) as well as a selection of relevant publications (possibly a self-authored monograph and up to five essays) must be submitted exclusively via the university’s Appointment Portal (https://berufungen.uni-tuebingen.de) by September 30, 2026. Enquiries may be directed to the Dean of the Faculty of Humanities, Prof. Dr. Angelika Zirker (berufungen@philosophie.uni-tuebingen.de).

We invite applications for up to 

three PhD positions (f/m/d, TV-L E13, 75%, 3 years) 

within the interdisciplinary research project EXPRESSO (Extracting Probabilistic Representations in Exponential Quantum Spaces). The aim of the project is to develop machine learning methods to tackle the exponential complexity of quantum state, design, and model spaces to fundamentally improve the quality of quantum simulations and quantum hardware design. It is conducted in the framework of the Cluster of Excellence – Machine Learning for Science and run jointly by researchers from the Institute for Theoretical Physics, the Computer Science Department, and the AI Center at the University of Tübingen.

The PhD projects are:

• Probabilistic simulation and inference for quantum gases
• Simulation-guided model discovery via adaptive amortized inference
• Representation learning for optimization in exponential search spaces

All projects are tightly integrated and offer supervision across both physics and machine learning. The principal investigators of the EXPRESSO project are

Philipp Hennig (Probabilistic Numerics), philipp.hennigspam prevention@uni-tuebingen.de
Mario Krenn (Automated Experiment Discovery), mario.krennspam prevention@uni-tuebingen.de
Igor Lesanovsky (Quantum Many-Body Physics), igor.lesanovskyspam prevention@uni-tuebingen.de
Jakob Macke (Simulation-Based Inference), jakob.mackespam prevention@uni-tuebingen.de
Georg Martius (Optimisation & Representation Learning), georg.martiusspam prevention@uni-tuebingen.de

Candidates should hold a Master's degree in Physics, Computer Science, Mathematics, or a related field, and have strong mathematical foundations and programming skills. Prior experience in quantum mechanics, Bayesian methods, or deep learning is an advantage. Applicants are expected to demonstrate commitment to interdisciplinary and impactful research, including a willingness to build concrete software artifacts.

Applications are reviewed on a rolling basis. Early applications are strongly encouraged. The review period closes on 14 September 2026.

Please upload a CV, a short motivation letter and the names of two Referees here https://forms.gle/JLVdK2Vi8bmmjsu29. Also indicate your preferred project(s).