Senior Researcher: Machine Learning – Microsoft Research AI for Science

Deep learning has only just started its transformative impact on the natural sciences. In Microsoft Research AI for Science we are seeking to solve some of the fundamental challenges in the molecular sciences with deep learning.

For our lab Berlin, Germany or Cambridge,UK-we are seeking exceptional Machine Learning Researcher candidates for a moonshot project in the field of molecular biology. If you are passionate about this research area and believe you can make a lasting impact, we would love to receive your application.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

This post will be open until the position is filled. When submitting your application, include your CV with a list of publications as an attachment. 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.
   

#Research #AI for Science

• 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.