Overview
At 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 software engineer to join our density functional theory (DFT) team (). The mission of the team is to enable highly accurate and scalable predictions of the energy and density of electrons in molecules and materials with deep learning powered DFT. Accurately computing the electron energy 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 advancing the capabilities of deep-learning-based DFT simulations through state-of-the-art numerical algorithms, GPU acceleration and integration of our models in highly performant DFT software frameworks, you will help unlock new frontiers in materials science, catalysis, and beyond. Learn more about our work on accurate and scalable DFT in and our .
This post will be open until the position is filled.
Qualifications
Required Qualifications:
1. MSc in computer science, mathematics, physics, chemistry, or a related area.
2. Proficiency in collaborative software engineering in Python and in C++ or Fortran.
3. Experience with maintenance of open-source libraries or commercial software packages.
4. Understanding CPU and GPU compute architecture fundamentals.
5. 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: :
6. PhD degree in computer science, mathematics, physics, chemistry, or a related area or comparable industry experience.
7. Experience with CUDA programming.
8. Experience with developing and optimizing numerical methods for high-performance computing platforms.
9. Experience with development of high-performance DFT or quantum chemistry software.
# Microsoft research #AI for Science
Responsibilities
10. Collaborate with internal and external parties on integrating our deep learning models in high performance DFT software frameworks, targeting both CPU and GPU-based frameworks.
11. Prepare and maintain open-source releases and releases for beta testers.
12. Write custom efficient GPU implementations for our deep learning models.
13. Work cross-functionally with deep learning and quantum chemistry researchers and engineers to align model development strategies with high-performance integration into CPU and GPU-based DFT software frameworks.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect