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Research Intern on BioEmu

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Microsoft Corporation

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Location:
Germany , Berlin

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Category:
Research and Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We seek passionate and highly motivated interns for the Biomolecular Emulator (BioEmu) project. 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 (see our blog post for links to our open-source software and other resources, as well as this explainer video).

Job Responsibility:

  • Design and implement machine learning models to capture protein structure, dynamics, and interactions
  • run ablation studies and baselines to validate ideas
  • Curate and build datasets (e.g., structural/biophysical data) and develop robust data pipelines suitable for large‑scale training and evaluation
  • Define and refine evaluation metrics/benchmarks where none exist
  • analyze failure modes and quantify uncertainty
  • Contribute high‑quality research code in shared Python codebases (e.g., PyTorch/NumPy/SciPy/Pandas), emphasizing reproducibility and clarity
  • Collaborate across disciplines (machine learning, structural biology, biophysics)
  • communicate results clearly to diverse collaborators
  • present findings in group forums
  • Aim for impact: help translate research artifacts (models, datasets, papers, blog posts) for broader community use

Requirements:

  • Advanced degree or current PhD enrollment in machine learning, AI, Physics, Chemistry, biophysics, structural biology, or a related field
  • Hands‑on experience developing machine learning models
  • Proficiency in collaborative Python development on shared research codebases
  • Strong communication skills to work effectively in an interdisciplinary team and explain technical concepts to collaborators from diverse backgrounds

Nice to have:

  • Experience working with and evaluating models such as AlphaFold and Boltz
  • Experience with diffusion models (training, sampling, evaluation)
  • Experience designing and producing large‑scale datasets for ML (e.g., curating structural biology or biophysical datasets, establishing data quality criteria, and building scalable loaders)

Additional Information:

Job Posted:
February 14, 2026

Work Type:
On-site work
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