Expoint - all jobs in one place

Finding the best job has never been easier

Limitless High-tech career opportunities - Expoint

Microsoft Senior Researcher Machine Learning – Microsoft Research AI Science 
United Kingdom, England, Cambridge 
902955604

10.12.2024

A completed or nearly completed PhD or comparable industry research experience is expected.

Required

  • Experienced in Python software development with object-oriented design and basic deployment, ideally demonstrated by published software projects (e.g., github).
  • Experienced in developing and implementation of deep learning systems (e.g., in PyTorch or JAX).
  • Experienced in modelling or simulation of molecules, ideally biomolecules.
  • High-quality publications in leading disciplinary or interdisciplinary journals or conferences.

Preferred

  • Experience with protein science or bioinformatics.
  • Experience with interpreting and including experimental data into models, e.g., Cryo-EM.
  • Understanding of computational statistics and experience with generative model development (e.g., diffusion or flow-models).
  • Experience in method development for molecular dynamics and statistical mechanics.
  • Track-record of developing and optimizing novel deep learning architectures.
Responsibilities
  • Contribute to and drive an ambitious, high-impact, research agenda development on machine learning in the molecular sciences.
  • Develop efficient and expressive machine learning models for biomolecules.
  • Develop strategies for integrating large-scale heterogeneous model data from molecular simulation and laboratory experiments, and identifying untapped data sources.
  • Write research code to test new approaches or develop novel theoretical and practical insights.
  • Prepare technical papers and presentations.
  • Working on a day-to-day basis with an international and interdisciplinary research team on one overarching research goal.
  • Being fully committed to one research project that may take several years to come to fruition and prioritizing team success over individual research interests.