Meta's Fundamental AI Research organization (FAIR) is developing AI-based methods to accelerate novel material discovery. In this position, you will be joining the AI for Chemistry team doing this work. The material domains currently being worked on are electro-catalysts for CO2RR & OER, nano-porous materials for direct air capture, and new materials for display technologies.
You will be a researcher for AI modeling of display materials. The role will be performed in close collaboration with computational and experimental chemists in Reality Labs Research and AI researchers in FAIR. You will be expected to provide technical leadership across large-scale Ab initio simulations, data generation and management for ML training, ML modeling, and applying ML models to material discovery.
The work being done will in some cases be published and open-sourced. This role may also be done jointly with several university chemical engineering departments. The aim of the work is to go end to end from computational discovery to productizing new materials, so you will have the opportunity to work across that entire lifecycle.
Research areas may include Machine Learning, Graph Neural Networks, Graph learning, Density Functional Theory, Computational chemistry, Optics, or other similar fields.
This role offers the opportunity to work on cutting-edge AI applications in chemistry and material science, with a focus on display materials. You'll collaborate with experts in both AI and chemistry, contribute to open-source projects, and potentially work with university partners. The position spans from computational discovery to product development, providing a comprehensive experience in AI-driven material innovation.