ML Research Intern

The role:

• Extend and scale Diffuse’s in-house deep generative modeling toolkit for downstream applications in molecular design.
• Thoughtfully execute deep learning experiments to improve performance of models or develop new functionality (e.g. loop engineering, structure prediction of protein-protein complexes).
• Have ownership of a scoped-out project centered on advancing internal methods.
• Located in the Bay Area (remote work is an option for exceptional candidates).
• 4 month minimum (3 months for exceptional candidates).

Ideal background:

• Self-starter who enjoys working on tough scientific problems and is results-driven.
• Able to think critically, methodically, and creatively about experiments.
• Proficient in Python.
• Experience working with deep learning frameworks (e.g., PyTorch).
• Track record of impressive work in industry/academia centered on ML / deep learning.
• Currently pursuing a graduate degree in math, CS, stats, bioengineering, comp bio, or a related field (not a hard requirement for exceptional candidates).
• Industry experience in a data science or engineering position

Pluses:

• Knowledge of physics, math, molecular biology, chemistry, etc.
• Previous work on ML applied to problems in structural biology or molecular design.
• Strong publication record.

What we offer:

•  The opportunity to work on cutting-edge AI with leading researchers from top institutions.