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Senior Machine Learning Researcher - MSR AI for Science

https://www.microsoft.com/ Logo

Microsoft Corporation

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Location:
United Kingdom , Cambridge

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

At 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 ML Researchers to join our Biomolecular Emulator (BioEmu) and Small Molecules Drug Discovery 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. Our BioEmu-1 model was published in Science. In our Small molecules - Microsoft Research work we build and apply large ML and LLM algorithms to accelerate the discovery of small molecule drugs and materials. Our team encompasses people from multiple disciplines across machine learning, engineering, and the natural sciences, who work together closely on well-defined and challenging goals. If you have strong machine learning expertise and enjoy designing and creating tools for scalable machine learning research for the natural sciences, please apply.

Job Responsibility:

  • Invent novel deep learning techniques for models of (bio)molecular structure, dynamics, reactivity and function
  • Design, implement, and iterate on model architectures and training algorithms (e.g., diffusion/sequence–structure models, language models, representation learning)
  • run rigorous ablations and baselines
  • Define success where standards don’t exist yet: proposing sound benchmarks and uncertainty‑aware metrics that reflect real‑world utility
  • Build high‑quality research code (Python/PyTorch) with reproducible workflows and robust data pipelines
  • Partner across disciplines—communicate clearly with ML researchers and experimental/computational biologists/chemists
  • present results and influence direction
  • Work autonomously and as a team player, reporting insights, risks, and next steps with crisp written/visual summaries
  • Thrive with imperfect, heterogeneous data, using principled curation, augmentation, and probabilistic evaluation
  • Aim for impact: try ideas quickly and fail-fast when they don't work. Rapidly convert working ideas to artifacts others can use (code, models, datasets, papers, patents)

Requirements:

  • PhD or equivalent research experience in Computer Science, Machine Learning, Physics, Chemistry, or a related field
  • Demonstrated leadership in ML architecture and algorithm design
  • Strong expertise in deep learning (model design, large-scale training, evaluation and reproducibility), statistics and linear algebra
  • Proficiency in Python and modern ML/scientific frameworks (e.g., PyTorch, JAX, TensorFlow, NumPy, SciPy, Pandas)
  • Peer-reviewed publications in leading venues (e.g., NeurIPS, ICML, ICLR or leading journals)
  • Excellent technical communication for collaborating in an interdisciplinary team
  • Curiosity and drive to apply deep learning to problems in biology or chemistry
  • Comfort with real‑world, noisy/heterogeneous data

Nice to have:

  • ML Engineering skills (e.g., model optimization and deployment, code design, CUDA)
  • Experience with geometric DL, reinforcement learning, generative models or large language models
  • Experience with biomolecular modeling or bioinformatics (e.g., folding systems, structural analysis/visualization, MD simulation, structure/genome databases) and/or chemical modelling (2D/3D structures), chemoinformatics and computational chemistry
  • Ability to work with and interpret real‑world biological data (e.g., cryo‑EM, protein binding affinities, structural/biophysical/chemical measurements, molecular data)

Additional Information:

Job Posted:
January 05, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
Job Link Share:

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