Open positions

Subject to final approval as part of the interdisciplinary project ‘Human-Centered Agentic Science’, the Everyday Media Lab is offering a

PhD Position (m/f/d)Part-time 75%, fixed term for three years (one year extension negotiable), 

starting January 2027 or later (the latest April 2027).

The Everyday Media Lab investigates (incidental) knowledge processes that occur when people engage with social media or communicative AI, whether in everyday life or in professional contexts. Human-Centered Agentic Science is an interdisciplinary project funded through the Innovation Fund Program of the Cluster of Excellence – Machine Learning for Science. The project is run jointly by researchers from different departments of the University of Tübingen (Prof. Dr. Carsten Eickhoff and Dr. Harrisen Scells (both Health NLP Lab); Prof. Dr. Christoph Bareither (Cultural Anthropology and Digital Anthropology)).

The successful candidate will work alongside three other PhD students (two from computer science and one from anthropology) on the question of how agentic AI can be integrated into the research process. The subproject Advancing Human-centered Agentic Science through Psychological Approaches at the IWM focuses on potential unintended effects of agentic science. These effects will be studied on three levels: researcher’s motivation, researcher’s reputation within the scientific community, and broader societal perceptions. The successful candidate will conduct surveys and experiments among scientists from various disciplines as well as members of the general public. Once prototypes have been developed within the first two subprojects, additional studies with test users will be carried out. The subprojects are tightly integrated and require interdisciplinary collaboration.

Your responsibilities will include designing, conducting, and analyzing empirical studies, presenting findings at national and international conferences, and publishing in peer-reviewed international journals. Participation in regular events organized by the Cluster of Excellence - Machine Learning for Science is expected. You will also be involved in the establishment/expansion 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 are consolidated and networked with other institutions. In addition, you will support the administrative management of the lab. Writing your doctoral thesis on a self-generated research question in one of the research areas of the lab is desired and explicitly supported.

Your profile:

• Above-average degree (Master's or equivalent) in psychology, cognition science or related disciplines
• Experience in the design, planning, conduction and analysis of quantitative empirical studies
• Interest in machine learning / agentic AI and working in interdisciplinary teams and contributing to a culture of shared learning
• Self-motivated and pro-active working style with an open and curious mindset
• Very good command of English; knowledge of German is an asset

We offer:

• An exciting and varied field of research with creative freedom in an interdisciplinary and internationally oriented research institute located in central Tuebingen (Germany)
• Work in an cooperative an enthousiastic team as well as a stimulating, international and interdisciplinary oriented research environment
• Remuneration based on the collective agreement for the public service in the federal states of Germany, including the social benefits customary in public service
• Employment, remuneration (pay group 13 TV-L) and social benefits, including company pension scheme and 6 weeks annual leave, are based on the collective agreement for the public service in the federal states of Germany (TV-L)
• Reconciliation of work and family life, family-friendly working hours, cost subsidy for pre-school childcare
• Mobile working option (hybrid), subsidy towards the Deutschlandticket as a job ticket, occupational health management (OHM)

Apply now

For more information, please do not hesitate to contact Prof. Dr. Sonja Utz by phone +49 7071 979-308 or email: s.utzspam prevention@iwm-tuebingen.de.

Please send your application in a single PDF file with the covering letter, curriculum vitae and certificates by quoting reference number 1013-2026 to careerspam prevention@iwm-tuebingen.de. Preference will be given to applications received by October 9th, 2026.

The IWM is committed to equality for all people and therefore expressly welcomes applications regardless of age, disability, ethnic, cultural or social background, gender, religion, belief or sexual identity. Applications from equally qualified candidates with disabilities will be given preference.

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 31^st 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.

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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