Research Scientist, Life Sciences (Computational)
San Francisco, CA
Posted 14d ago
About the job
Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries by combining cutting-edge AI with hands-on biological research. We are seeking an exceptional Research Scientist to join this high-impact team, operating at the intersection of computational and experimental biology. This role offers a unique opportunity to shape how AI transforms biological research, working with leading AI researchers on problems that matter deeply for scientific understanding and biomedicine. You will have substantial access to Claude and will help establish how computational biology operates at Anthropic, guiding the development of transformative AI systems.
Responsibilities
- Build, run, and maintain analysis pipelines for sequence analysis, structural bioinformatics, phylogenetic and comparative genomics, high-throughput functional screens, and biological sequence modeling.
- Partner with experimental biologists to design experiments, generate high-quality data, and rapidly inform subsequent experimental steps.
- Generate and prioritize hypotheses for experimental follow-up using literature, biological knowledge bases, and primary data.
- Establish and maintain the team's computational infrastructure, including data ingestion, workflow orchestration, internal databases, and accessible interfaces.
- Utilize Claude and internal agent frameworks for personal work and provide feedback to model-improvement and product teams.
- Adapt to shifting priorities by picking up analyses across projects, demonstrating breadth and flexibility.
Requirements
- PhD in computational biology, bioinformatics, genomics, biophysics, machine learning, computer science, or a related quantitative or biological field, or equivalent industry research experience.
- Proven track record of leading computational biology research end-to-end, with evidence of impact (e.g., publications, preprints, released datasets/tools).
- Demonstrated breadth across multiple areas of computational biology.
- Proficiency in scientific computing programming languages and experience with large datasets in Linux and cloud environments.
- Ability to scope analyses for ambiguous biological questions and produce actionable results for experimentalists.
- Skill in clearly communicating computational results to both biologists and ML researchers.