Publisher
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Roland Aydin

3 weeks ago

Fully Funded PhD and Postdoctoral Positions in Foundation Models and Agentic AI for Physical Systems Saarland University in Germany

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

Fully funded PhD and postdoctoral positions.

Deadline

Aug 15, 2026

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Country

Germany

University

Saarland University

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Materials Science
Mathematics
Computational Science
Design Engineering
Physics
Applied Mathematic
Multi-agent System
Machine learning

About this position

Roland Aydin, Full Professor (W3) at Saarland University, is recruiting multiple fully funded PhD and postdoctoral researchers to work on Foundation Models and Agentic AI for Physical Systems.

The positions focus on developing AI systems that can reason about scientific problems, interact with simulations, and accelerate discovery in science and engineering. Research directions include LLMs & Scientific Agents, AI for Scientific Computing, Autonomous Engineering Design, Multimodal Scientific AI, AI Alignment, and AI for Materials Research.

Successful candidates will join one of Europe’s leading AI ecosystems across Saarland University, DFKI, and the Saarland Informatics Campus, with collaborations involving EPFL and Hamburg University of Technology. The post is especially relevant for applicants with backgrounds in Machine Learning, Computer Science, Physics, Materials Science, Applied Mathematics, or Computational Engineering.

Location: Saarbrücken, Germany. Funding: fully funded PhD and postdoctoral positions. Deadline: 2026-08-15.

Applicants should review job offers W2878 and W2879 on the Saarland University website and use the provided contact information if interested.

Funding details

Fully funded PhD and postdoctoral positions.

What's required

Outstanding candidates with backgrounds in Machine Learning, Computer Science, Physics, Materials Science, Applied Mathematics, Computational Engineering, or related fields are sought. Applicants should be excited about pushing the boundaries of multi-agent systems, foundation models, and AI for scientific and engineering problems.

How to apply

Refer to job offers W2878 and W2879 at uni-saarland.de and use the linked post/job description for contact information. Interested candidates should review the attached description and reach out if appropriate.

More information can be found here

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