Cluster of Excellence – Machine Learning for Science

Open positions

Currently there are several positions to be filled.

PhD student (m/f/d, 13 TV-L, 75%)

The International Centre for Ethics in the Sciences and Humanities (IZEW) at the University of Tübingen is currently seeking to fill the post of

PhD student (m/f/d, 13 TV-L, 75%),

available with immediate effect.

The post is funded by third-party grants and is fixed-term until 31 December 2029. Subject to a successful evaluation, the post may be extended up to 12 months.

 

The IZEW is an international, interdisciplinary research centre at the University of Tübingen that examines ethical issues arising within and from the sciences. We address the full spectrum of applied ethics. This includes topics such as AI, sustainable development, digitalisation, media and security. In addition to academic research and teaching, the IZEW pays particular attention to the transfer of findings from research in the ethics of science to the education sector and the general public.

The PhD student is based at the newly established Chair of ‘Ethics of Scientific and Technological Innovation’ at the International Centre for Ethics in the Sciences. Close collaboration with the ‘Norms & Practices Lab’ of the Cluster of Excellence ‘Machine Learning – New Perspectives for Science’ is planned. The successful candidate will work on a research project concerning ethical standpoints in large language models (LLMs), focusing in particular on issues of diversity, under the supervision of Prof. Sabine Ammon.

 

Responsibilities include: 

  • Contributing to the chair’s research focus on ethical perspectives in LLMs

  • Pursuing a PhD in the subject area of the research focus

  • Publishing, conference presentations and activities in science communication

 

Required qualifications:

  • A successfully completed academic degree in philosophy, computer science, or thematically related disciplines

  • Major areas of study in the philosophy of language, philosophy of technology, ethics of technology, AI ethics, philosophy of science and/or feminist philosophy

  • Basic programming skills and experience in prompting large language models (LLMs), or a willingness to learn these skills quickly

  • Basic knowledge of statistics, or a willingness to learn these skills quickly

  • A passion for interdisciplinary collaboration 

  • Very good command of English

  • Ability to work as part of a team and to work independently

If you have any enquiries regarding the post, please contact Dr. Mone Spindler (mone.spindlerspam prevention@izew.uni-tuebingen.de) or Prof. Sabine Ammon (ammonspam prevention@izew.uni-tuebingen.de).

People with severe disabilities will be given preferential consideration where equally qualified. The University of Tübingen is committed to the goals of equality and diversity and actively promotes equal opportunities. The University aims to increase the proportion of women in research and teaching and therefore encourages suitably qualified female researchers to apply.

Please submit your application, comprising the standard documents (cover letter, tabular CV, certificates, an extract from your Master’s thesis and a term paper, a brief outline of a potential PhD topic, references and your proposed start date), consolidated into a single PDF document, by email by 30 September 2026 to: mone.spindlerspam prevention@izew.uni-tuebingen.de.

Recruitment is handled by the Central Administration of the University of Tübingen.

Doctoral position (m/f/d; TV-L E13, 75%)

Open doctoral position within the research project “Human-Centered Agentic Science" at the Ludwig Uhland Institute for Historical and Cultural Anthropology within the Framework of the Excellence Cluster „Machine Learning: New Perspectives for Science“. At the University of Tübingen (Germany), Ludwig Uhland Institute for Historical and Cultural Anthropology, there is a 

doctoral position (m/f/d; TV-L E13, 75%) 

available. The position is to be filled as of January 1, 2027, or as soon as possible thereafter, no later than April 1, 2027. The position is limited to 36 month and can be extended for additional 12 months after positive evaluation.

 

Main Tasks:

* Independent research and development of a doctoral dissertation within the interdisciplinary project “Human-Centered Agentic Science,” with a focus on digital anthropology, science and technology studies (STS), and ethnographic research. The doctoral position is part of the Cluster of Excellence “Machine Learning: New Perspectives for Science” and involves working in an interdisciplinary team comprising researchers from digital anthropology/STS (Prof. Dr. Christoph Bareither), computer science (Prof. Dr. Carsten Eickhoff and Dr. Harrisen Scells), psychology (Prof. Dr. Sonja Utz) and Neuroscience (Prof. Dr. Kerstin Ritter), and will collaborate with several other disciplines like linguistics, economics, and physics. Using ethnographic approaches, the doctoral position will study and support the development and implementation of AI-based systems in the context of the automation of scientific workflows. In particular, it examines how ethnographic perspectives can contribute to the development of AI-based models for agentic science, to their productive implementation in scientific contexts, and, at the same time, to the necessary critique of the automation of scientific work. The goal is to demonstrate how ethnographic analysis and critical reflection on human-technology relationships can help shape the application of human-centered agentic science.

* Expansion/establishment and co-supervision of an interdisciplinary “Hub for Human-Centered Agentic Science,” in which activities in the field of agentic science within the Cluster of Excellence “ML for Science” are consolidated and networked with other institutions.

* Participation in regular events organized by the Cluster of Excellence “Machine Learning: New Perspectives for Science” (https://uni-tuebingen.de/en/133840) as well as in the “Digital Anthropology Lab” at the University of Tübingen: (www.digitalanthropologylab.org)

 

Requirements:
* A master’s degree with a very good grade in cultural anthropology/European ethnology, or

* A master’s degree with a very good grade in related subjects and fields, such as science and technology studies (STS), sociology, ethnology, or media studies.

* Strong expertise in ethnographic and/or qualitative social science research
* very good English language skills

 

Advantageous are:

* Previous experience in the research field of digital anthropology and/or science and technology studies 

* German language skills

 

The University of Tübingen is committed to the goals of equality and diversity and actively promotes equal opportunity. Equally qualified applicants with disabilities will be given preference. The university seeks to raise the number of women in research and teaching and therefore encourages qualified women to apply for these positions. Employment will be carried out by the central administration of the University Tübingen. 

 

Application documents

* Cover letter with curriculum vitae (Tabular Format)

* Graduation certificate (high school or similar), BA certificate, MA certificate (university), transcript of records.

* MA thesis

 

Application

Please send your application via email in one PDF document by October 1, 2026 to:

Prof. Dr. Christoph Bareither

Institute of Historical and Cultural Anthropology

University of Tübingen

Burgsteige 11

72070 Tübingen (Germany)

07071-297-2373

christoph.bareitherspam prevention@uni-tuebingen.de

HPC Systems Engineer – Security Architecture & Cluster Administration (m/f/d, E13 TV-L, 100%)

The Cluster of Excellence "Machine Learning - New Perspectives for Science" together with the Tübingen AI Center at the University of Tübingen offers a position as

HPC Systems Engineer – Security Architecture & Cluster Administration (m/f/d, E13 TV-L, 100%)

The position is available in the team of the Machine Learning Science Cloud and runs until 31st December 2032.

About Us 

The ML Cloud team designs, runs and safeguards high-performance computing infrastructure tailored to machine learning workloads. Our state of the art systems are distributed across four data centers for the Tübingen AI Center, the Cluster of Excellence ’Machine Learning: New Perspectives for Science’ and the Hertie Institute for AI in Brain Health. Every day, researchers unleash thousands of compute jobs on our systems, training frontier-scale neural networks and running experiments.

The Opportunity

Traditionally, HPC environments prioritized only performance and open access, with security as an afterthought. As our clusters grow and handle increasingly sensitive research data, security becomes mission-critical. We are looking for an HPC System Engineer who combines hands-on cluster operations with a security mindset. You will actively shape the security architecture of a live, production HPC / ML environment, keep our systems hardened, and build the processes and infrastructure that protect researchers, their data and their compute against a fast-evolving threat landscape.

Your Tasks

  • Design and operate our HPC clusters across four data centers, including scheduler (SLURM), parallel filesystems, networks and accelerators, ensuring high availability and throughput for research workloads
  • Conceive and establish the security architecture of the Machine Learning Science Cloud and harden the HPC environment
  • Evolve the automated provisioning and configuration of heterogeneous compute, storage and network nodes (e.g. image-based provisioning, node lifecycle)
  • Run patch and vulnerability management - risk assessment across heterogeneous systems
  • Build and operate logging, monitoring and intrusion detection, and integrate HPC telemetry into both operational dashboards and incident-response workflows
  • Lead incident response for the clusters: detection, containment, forensic support and post-incident review
  • Automate operations and security policy as code (Ansible/IaC)
  • Advice researchers on efficient, secure cluster usage (job scheduling, data handling, access workflows) and derive requirements for our further roadmap from their scientific workloads

Your Profile

  • Masters degree in Computer Science or a related field
  • In-depth IT security knowledge: system hardening, network security, applied cryptography and IAM - with the ability to derive architectural decisions from a threat model, not only to apply given baselines
  • Solid Linux experience in production environments (RHEL/Almalinux/Ubuntu)
  • Hands-on HPC background: Slurm, parallel file systems (Weka, Lustre, Ceph), GPU workloads and high-speed networks (InfiniBand, 400G Ethernet)
  • Experience with virtualization for management-plane and infrastructure services (Proxmox)
  • Strong scripting and automation skills (Bash, Python, Ansible) and experience with configuration management / Infrastructure-as-Code
  • A plus: security frameworks (ISO 27001, BSI Grundschutz), container security (Apptainer/Singularity/Docker) or offensive-security fundamentals
  • Independent, structured working style and good communication in English; German is a plus
  • A collaborative, user-facing mindset – comfortable supporting and advising researchers and translating their needs into platform design

What We Offer

  • Technically deep, architecturally open work that directly enables cutting-edge machine-learning research
  • Flexible working hours and the option to work partially from home
  • Working in an English-speaking, international team of HPC experts
  • A small, senior team with flat hierarchy where responsibility is split by domain
  • Ownership of a technical domain in a production environment of real scale
  • Professional development, conference attendance and real influence on our roadmap

Interested? We'd love to hear from you! 

Please submit your application, including CV and relevant transcripts by September 20, 2026 via our application portal careers.tuebingen.ai. For questions, please contact Simon Kreuzer at simon.kreuzerspam prevention@uni-tuebingen.de. The position is available from now on. Hiring is done by the Central Administration of the University of Tübingen. Severely disabled persons will be given preferential consideration if equally qualified. The University of Tübingen is committed to equity and diversity and actively promotes equal opportunities. The position is divisible.

Tenure-Track Professor for Philosophy of Machine Learning for Science

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).

PhD Positions in Quantum Physics and Machine Learning (f/m/d, TV-L E13, 75%, 3 years)

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).

 

Several open PhD and Post-Doc positions (m/f/d)
Mario Krenn

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 15.07.2026.

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.

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