Research Scientist Intern, FAIR Chemistry

Meta•San Francisco, CA

1d•$7,650 - $12,667

About The Position

Meta is seeking a Research Scientist Intern to join the FAIR Chemistry team, which develops AI-based methods for modeling the world at the atomic level. The team applies chemistry and materials science to areas such as energy sustainability, drug discovery, and new materials for display technologies. Internships last 12 to 16 weeks, or 24 weeks, and have various start dates throughout the year.

Requirements

Currently have or be in the process of obtaining a Ph.D. in Machine Learning, Chemistry, Chemical Engineering, Materials Science, Physics, Artificial Intelligence, or a relevant technical field.
Experience applying artificial intelligence to a scientific domain, such as computational photonics, computational design, or computational chemistry.
Experience devising data-driven models and real-system experiments and implementing designs 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 another related programming language.
Experience with deep-learning frameworks such as PyTorch, JAX, or TensorFlow.
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Nice To Haves

Intent to return to the degree program after completing the internship or co-op.
A proven record of significant results demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences such as NeurIPS, ICML, CVPR, ICCV, ICLR, or similar.
Experience solving analytical problems using quantitative approaches.
Ability to manipulate and analyze complex, large-scale, high-dimensional data from varying sources.
Experience using theoretical and empirical research to solve problems.
Experience conducting optimization using machine-learning and/or deep-learning methods.
Demonstrated software engineering experience through an internship, work experience, coding competitions, or widely used contributions to open-source repositories such as GitHub.
Experience working and communicating cross-functionally in a team environment.

Responsibilities

Advance the state of the art in AI for generative atomic world models.
Develop datasets to train and test AI models for chemistry.
Develop, train, and scale AI models for chemistry in PyTorch.
Run large-scale chemistry simulations.
Develop processes to feed experimental results back into chemistry models.
Optimize the efficiency of classic and machine-learning-based chemistry software.
Write research papers and provide associated open-source data and code releases.