Machine Learning Research Intern

The Machine Learning (ML) team at Profluent is looking for a creative and motivated intern to drive research into new technologies for protein design. This position offers an opportunity to leverage advances at the forefront of machine learning for language processing, geometric representation, and proteins. Interns will have broad exposure to the technologies across the platform, including cross-functional interactions with the wet lab and teams regularly deploying new models and algorithms towards specific protein design goals.

• →Contribute to ML research advancing the state-of-the-art in deep learning for protein sequence, structure, and function and its application to protein design
• →Work with a research mentor and the broader ML team to advance a summer research project for peer-reviewed publication or internal deployment
• →Analyze, interpret, and organize results and present progress to colleagues in regular research meetings

• Current PhD Student (or equivalent industry experience) in Applied Math, Computer Science, Computational Biology, Machine Learning, Natural Language Processing, Statistics, or a related field
• Experience with conceiving of, implementing, and developing novel machine learning methodology
• Experience with modern deep learning frameworks such as Pytorch or Jax

• Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
• Familiarity with foundational biology of proteins and nucleic acids
• Experience developing machine learning models for proteins (language models, structure prediction, design)