Research Scientist Intern, FAIR Chemistry (PhD)

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, machine learning, computational chemistry, graph neural networks, natural language processing, and generative modeling. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.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 electro-catalysts for CO2RR & OER, nano-porous materials for direct air capture, and new materials for display technologies.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

• 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.

• 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.

• Intent to return to 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.