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Microsoft Research AI for Science is seeking a talented software engineer to join our mission of accelerating scientific discovery through AI. By advancing the capabilities of deep-learning-based DFT simulations through state-of-the-art numerical algorithms and GPU acceleration, you will help unlock new frontiers in materials science, catalysis, and beyond. Learn more about our work on accurate DFT in our blog and about our GPU-accelerated DFT code in a paper.

This role is an exceptional opportunity to drive ambitious software development at the intersection of cutting-edge research and real-world deployment, with access to world-class infrastructure. Join a highly collaborative, interdisciplinary, and diverse global team of researchers and engineers that’s redefining what’s possible in quantum chemistry.

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

Required qualifications:

• MSc or PhD degree in computer science, mathematics, physics, chemistry, or a related area, or comparable industry experience.
• Proficiency in collaborative software engineering in Python and in C++ or Fortran.
• Experience with development of high-performance numerical algorithms.
• Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds.

Preferred qualifications:

• Experience with CUDA programming.
• Experience with development of high-performance quantum chemistry software.
• Experience with development of open-source libraries.

#Research #AI for Science

• Design and develop software for high-performance GPU-accelerated DFT simulations with deep-learning-based density functionals.
• Prepare and maintain open-source releases and releases for beta testers.
• Work cross-functionally with deep learning and quantum chemistry researchers and engineers to align model development strategies with high-performance integration into quantum chemistry software.