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Postdoctoral Researcher, BioEmu (Machine Learning & Molecular Biology) at Microsoft

Berlin, England, Germany -

Full Time

Start Date

Immediate

Expiry Date

21 Dec, 25

Salary

0.0

Posted On

22 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Molecular Biology, Biomedical Impact, Scientific Modelling, Drug Discovery, Protein Dynamics, Structural Biology, Collaboration, Innovation, Optimization

Industry

Software Development

Description

At Microsoft Research AI for Science [https://www.microsoft.com/en-us/research/lab/microsoft-research-ai-for-science] , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs. We seek a highly motivated Postdoctoral Researcher to join our Biomolecular Emulator (BioEmu) team. The BioEmu project aims to model the dynamics and function of proteins --- how they change shape, bind to each other, and bind small molecules. This approach will help us to understand biological function and dysfunction on a structural level and lead to more effective and targeted drug discovery. Our BioEmu-1 model was published in Science [https://www.science.org/doi/10.1126/science.adv9817] (see our blog post [https://www.microsoft.com/en-us/research/blog/exploring-the-structural-changes-driving-protein-function-with-bioemu-1] for links to our open-source software and other resources and this explainer video [https://www.youtube.com/watch?v=LStKhWcL0VE]). WHY THIS ROLE IS EXCITING You’ll work on problems that don’t yet have well‑defined benchmarks. Where part of the innovation is deciding what to optimise and proving it matters for biology. It’s an opportunity to bridge state‑of‑the‑art ML with meaningful biomedical impact in a highly collaborative research environment.

Responsibilities

The Postdoctoral Researcher will work on modeling the dynamics and function of proteins to understand biological function and dysfunction. This role involves bridging machine learning with biomedical impact in a collaborative research environment.