Co-Op, AI Nucleic Acid Design

What you'll do

• Build and investigate ML models for nucleic acid sequence-function prediction, generative design, or candidate selection.
• Analyze model behavior and develop biological hypotheses; explore reasoning models for scientific discovery and sequence design.
• Collaborate with experimental scientists, propose experiments, and present or write up research findings.

What they ask for

• Currently enrolled in an MS or PhD program in a quantitative field such as machine learning, computational biology, bioengineering, computer science, or statistics.
• Hands-on experience building and training ML models; strong Python skills and experience with PyTorch, JAX, or a similar framework.
• Coursework or research experience with biological sequence data (DNA or RNA).
• Available for a full-time, 6-month co-op term onsite in San Francisco.

Nice to have

• Experience with sequence-to-function or genomic language models, functional genomics data, RNA structure prediction, sequence design, or generative modeling and optimization.
• Experience with wet-lab data, scientific reasoning models or AI agents, or a research publication, preprint, or open-source project.

Tools

Python, PyTorch, JAX

AI focus

Develop ML models for nucleic acid sequence-function prediction and design; explore large reasoning models to generate hypotheses, reason over experimental results, and guide sequence design.