Research Scientist, AI for Science (PhD)

Meta is seeking a Research Scientist to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI, on the Chemistry team. The Chemistry team develops AI-based methods to accelerate materials and molecular discovery for climate and AR/VR applications. 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.Currently has or is in the process of obtaining a PhD in the field of Machine Learning, Computer Science, Physics, Artificial Intelligence, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta Experience applying artificial intelligence to a scientific domain such as computational photonics, computational design, computational chemistry, etc Experience devising data-driven models and real-system experiments and design implementation for AI design and optimization Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures Experience with Python, C++, C, Julia, or other related language Experience communicating complex research for public audiences of peers Experience with frameworks such as Pytorch, Jax, or Tensorflow Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, CVPR, ICCV, ICLR, or similar Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta Experience in identified research areas such as artificial intelligence, machine learning, AI applied to chemistry or material science, computational statistics, and applied mathematics Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub) Experience solving analytical problems using quantitative approaches Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources Experience in utilizing theoretical and empirical research to solve problems Experience doing optimization based on machine learning and/or deep learning methods Experience solving complex problems and comparing alternative solutions, tradeoffs, and broad points of view to determine a path forward Experience working and communicating cross functionally in a team environment Experience in areas such as deep learning, generative models, graphical models, reinforcement learning, computer perception, natural language processing and data representation