Meta is seeking Research Interns to join the FAIR Chemistry team. The Chemistry team develops AI-based methods to accelerate novel materials discovery. The material domains currently being worked on are catalysts for renewable energy and green hydrogen applications, nano-porous materials for direct air capture, and new materials for display technologies. Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, FAIR Chemistry (PhD) Responsibilities
- Advancing the state-of-the-art in AI for atomic world models and material generation.
- Developing datasets to train and test AI models for Chemistry.
- Developing, training, and scaling AI models for Chemistry in PyTorch.
- Running large-scale chemistry simulations.
- Developing processes to feedback experimental results into chemistry models.
- Efficiency optimization of classic and ML based chemistry software.
- Writing research papers and associated open source data and code releases.
Minimum Qualifications
- Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Chemistry, Chemical Engineering, Physics, Artificial Intelligence, or relevant technical field.
- 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 with deep learning frameworks such as Pytorch, Jax, or Tensorflow.
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
Preferred Qualifications
- Intent to return to the degree program after the completion of the internship/co-op.
- 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.
- Experience solving analytical problems using quantitative approaches.
- Ability to manipulate and analyze 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.
- Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
- Experience working and communicating cross functionally in a team environment.
For those who live in or expect to work from California if hired for this position, please click here for additional information.
