AI Chemistry Research Intern — Generative Atomic Models

Meta; San Francisco (CA); On-site; USD 33,000 - 56,000; Full time

Job summary

Meta's FAIR Chemistry team invites Research Scientist Interns to help push AI for chemistry and materials science. You will develop and train AI models in PyTorch, build datasets, and run large-scale simulations to advance atomic world models.

The internship spans 12–24 weeks with flexible start dates throughout the year, offering hands-on research with real-world applications. You will collaborate across disciplines, contribute to open-source data, and publish findings while gaining mentorship

Qualifications

• Pursuing or obtained a Ph.D. in ML, Chemistry, Chemical Engineering, Materials Science, Physics, or related field.
• Experience applying AI to scientific domains such as computational chemistry or materials design.
• Strong research communication and collaboration skills.

Responsibilities

• Advance state-of-the-art in AI for generative atomic world models.
• Develop datasets to train and test AI models for Chemistry.
• Train and scale AI models for Chemistry in PyTorch.
• Run large-scale chemistry simulations.
• Develop processes to feedback experimental results into chemistry models.
• Optimize efficiency of chemistry software.
• Publish research papers and open source data/code releases.

Skills

AI/ML

PyTorch

Large-scale simulations

Scientific research

Education

Ph.D. degree in a relevant field

Tools

PyTorch

Job description

Meta's FAIR Chemistry team invites Research Scientist Interns to help push AI for chemistry and materials science. You will develop and train AI models in PyTorch, build datasets, and run large-scale simulations to advance atomic world models.

The internship spans 12–24 weeks with flexible start dates throughout the year, offering hands-on research with real-world applications. You will collaborate across disciplines, contribute to open-source data, and publish findings while gaining mentorship