AI Researcher​/Engineer

Project:MIND-MATTER

Duration:6 months (2026)

Location:Hybrid (Bremen / remote)

We are looking for anAI Researcher / Engineerto help build next-generation systems forautonomous scientific discovery. You will work on AI agents that can reason over scientific knowledge, design and run simulations, analyze results, and iteratively refine hypotheses — pushing toward the vision of anAI Scientist.

This role sits at the intersection ofAI systems, scientific computing, and materials research, within a high-risk, high-impact research programme exploring neuromorphic materials and “computation in matter”.

Build and integrate AI agents that autonomously explore scientific hypotheses

Connect AI reasoning systems to simulation and data analysis pipelines

Design infrastructure for managing experiments, simulations, and results

Develop tools for automated analysis, comparison of models, and visualization

Collaborate closely with experimentalists and researchers across Europe

The emphasis is onsystems thinking and autonomy, not narrow model tuning.

Background in AI, computer science, physics, materials science, or related fields

Strong Python skills and experience with scientific or ML workflows

Familiarity with modern AI tools (LLMs, agents, APIs, or ML frameworks)

Ability to work independently in open-ended research settings

Nice to Have

Experience with simulations, computational physics, or materials modeling

Cloud infrastructure, data pipelines, or automation experience

Interest in Bayesian methods, experiment design, or scientific reasoning

Real scientific impact: contribute to resolving open research questions

Autonomous AI: design systems that reason, act, and learn over long time horizons

Transferable methods: approaches applicable across materials, chemistry, and biology

Close collaborationwith leading researchers and experimental teams

MIND-MATTERinvestigates neuromorphic materials that perform energy-efficient analogue computing. The project pioneers anAI Scientistthat closes the loop from hypothesis → experiment → analysis → theory refinement, setting a blueprint for future self-driving labs.

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