Saarland University is an internationally recognized campus university with particular strengths in computer science, artificial intelligence and the materials and life sciences. With over 17,000 students and more than 4,000 staff, it is one of the largest employers in the region and an officially recognized family-friendly university.
The newly established Chair of Data-Driven Simulation and Analysis in Materials Science (Prof. Dr. Roland Aydin) at Saarland University, jointly affiliated with the German Research Center for Artificial Intelligence (DFKI), is inviting applications for
Several fully funded PhD / Post-Doctoral Positions (m/f/x)
Foundation Models and Agentic AI for Physical Systems
Reference number W2878 (PhD) and W287G (PostDoc), salary in accordance with the German TV-L salary scale1, pay grade E13 TV-L, 100% of standard working time, duration: 3 years for PhD positions, 3 years for PostDocs (with the option of extension).
As a point of reference: E13 TV-L starts (if no relevant prior experience) at €57.112 gross per year, not including annual special payments.
What we work on
Our group develops LLMs and agentic AI systems for scientific discovery, engineering and physical systems. We investigate how AI can reason about scientific problems, interact with simulation software and support the design of complex physical systems. The group is jointly embedded at Saarland
University and DFKI in Saarbrücken as well as the Saarland Informatics Campus with close ties also to other research institutes, thus offering access to one of Europe’s leading AI ecosystem, with modern compute infrastructure.
Current research directions include
- AI for scientific computing – neural operators and learning-based surrogates for physical systems
- LLMs and scientific agents – large language models that autonomously reason, plan and execute scientific workflows
- AI for engineering design – LLM-driven agents for autonomous optimisation and design of materials, structures and processes
- Multimodal scientific AI – integrating language, images, sensor data and simulations
- Alignment for scientific AI – scalable oversight, verification and control of LLM-based agents
- AI for materials discovery – generative models, active learning and autonomous discovery of novel materials
We welcome applications from candidates whose interests align with one or more of these directions and who are excited about advancing the interface between AI and the natural sciences.
Your potential responsibilities
- Pursue an independent research project (toward your doctorate, or, as a PostDoc, develop your own research line) within one of the research directions above or a closely related area
- Develop, train and evaluate modern ML models on GPU/HPC infrastructure – including graph neural networks, transformers, neural operators, diffusion models and foundation-model-based systems –and, where relevant, combine them with numerical simulation and scientific computing workflows
- Publish at leading venues (e.g. NeurIPS, ICML, ICLR, AAAI, npj Computational Materials) and present your work at international conferences
- Contribute to collaborative research projects with our close partners at EPFL and at the Hamburg University of Technology, and, as a PostDoc, help shape future research initiatives and funding proposals
- Support teaching, co-supervise students (PhD/Master/Bachelor, as appropriate to your level) and collaborate actively across Saarland University, DFKI, the Saarland Informatics Campus, and international partners
Your profile
- For PhD positions: above-average Master’s degree (or equivalent) in Computer Science, Computational Engineering, Materials Science, Mechanical Engineering, Physics, Applied Mathematics or a closely related discipline
- For PostDoc positions: completed doctoral degree (PhD / Dr.-Ing. / Dr. rer. nat.) in one of the above disciplines, with a demonstrated research record at the interface of AI and science
- Solid foundations in machine learning and deep learning, together with an interest in scientific computing, numerical simulation, computational engineering or computational materials science
- Strong programming skills in Python, both with vibe coding and without, and experience with PyTorch (or JAX/TensorFlow) and the scientific-Python ecosystem
- Independent and structured working style, strong communication skills and genuine enthusiasm for interdisciplinary research
- Excellent English skills for research, scientific writing and collaboration (according to CEFR: C1); German is not required at the time of hiring
- Welcome additions: publications, open-source contributions, or hands-on experience with: diffusion models, foundation models, LLM fine-tuning, agentic AI systems, or scientific simulation software
What we can offer you
- A flexible work schedule allowing you to balance work and family, among other things the possibility of working remotely (part of the time)
- Secure and future-oriented employment with attractive conditions
- A broad range of further education and professional development programs (for example language courses)
- An occupational health management model with numerous attractive options, such as our university sports program
- Supplementary pension scheme (RZVK)
- Discounted tickets on local public transport services (‘Job-Ticket‘ of the saarVV)
- Job bike leasing (JobRad)
How to apply
Please send your application as a single PDF (max. 10 MB) with the level and reference number you are applying for in the subject line (W2878 - PhD or W287G – PostDoc) by August 15th 2026 to [email protected].
Please include
- A short motivation letter (1 page for PhD, up to 2 pages for PostDoc) stating which direction interests you most – or proposing your own
- A CV including publication list (PostDocs: please highlight your three most relevant papers)
- Master’s and Bachelor’s transcripts (PhD applicants); PhD certificate or confirmation of submission
(PostDoc applicants) - Names and contact details of two academic referees
- Optional: links to GitHub, personal website, or preprints
Contact: Prof. Dr. Roland Aydin, Saarland University – [email protected]
Pay-grade classification depends on the details of the position and the applicant’s qualifications under the TV-L scale; part-time employment is generally possible. Foreign degrees require an equivalence statement by the Zentralstelle für ausländisches Bildungswesen (ZAB) before hiring (see https://www.kmk.org/zeugnisbewertung); interview and ZAB costs cannot be reimbursed. We welcome applications regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, and sexual orientation and identity. In accordance with its policy of increasing the proportion of women, the University actively encourages applications from women; applications from severely disabled persons will be given preferential consideration in the event of equal suitability. By submitting your application you confirm that you have taken note of the Saarland University privacy notice (Art. 13 DSGVO).
