At Microsoft Research AI for Science we believe deep learning 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 research engineer with expertise in computational materials science to join our density functional theory (DFT) team. The mission of the team is to enable highly accurate and scalable electronic structure calculations in molecules and materials with deep learning powered DFT. Accurately computing the electronic structure at affordable cost is essential for predictive modelling of laboratory experiments across a broad spectrum of applications, including assessing whether a chemical reaction will proceed, whether a candidate drug molecule will bind to its target protein, whether a material is suitable for carbon capture, or if a flow battery can be optimized for renewable energy storage. By focusing on extending the capabilities of our deep-learning-based DFT simulations to solids, you will help unlock new frontiers in materials science, catalysis, and beyond. Learn more about our work on accurate and scalable DFT in our blog and our project website.

This post will be open until the position is filled.

• Implement and maintain evaluation pipelines for exchange correlation functionals for materials using software packages like VASP, CP2K, QuantumEspresso, FHI-aims, PySCF, or similar
• Work cross-functionally with deep learning and quantum chemistry researchers and engineers to build and maintain model evaluation and data generation pipelines for exchange-correlation functionals for materials.
• Prepare and maintain open-source releases and releases for beta testers
• Work cross-functionally with deep learning, quantum chemistry researchers and engineers to align model development strategies with high-performance integration into CPU and GPU-based DFT software frameworks for materials.

Required qualifications:

• Completed (or about to complete) PhD in physics, chemistry, computational sciences, mathematics, or a related area
• Experience with computational materials science, especially DFT and its limitations
• Development experience with DFT solid state software packages (VASP, QuantumEspresso, CP2K, FHI-aims,…)
• Proficiency in collaborative software engineering in Python and in C++ or Fortran
• Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds

Qualifications that are considered a plus, but are not strictly required:

• Experience with maintenance of open-source libraries or commercial software packages

#Research #AI for Science

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.