Research Scientist, Life Sciences
Research Scientist driving fundamental biological discoveries by building large-scale computational analysis pipelines, partnering with experimental biologists on hypothesis-driven research, and leveraging frontier AI models like Claude on petabyte-scale biological data. Requires PhD and end-to-end computational biology research track record with demonstrated breadth.
About the job
Key Responsibilities
- Build, run, and maintain analysis pipelines for experimental programs including sequence analysis at petabyte scale, structural bioinformatics, phylogenetic and comparative genomics, design and analysis of high-throughput functional screens, and biological sequence modeling.
- Partner directly with experimental biologists to design experiments that produce high-quality data and rapidly turn results around to inform the next experiment.
- Draw on scientific literature, curated biological knowledge bases, and primary data to generate and prioritize hypotheses for experimental follow-up.
- Stand up and maintain the team's computational infrastructure including data ingestion, workflow orchestration, internal databases, and interfaces accessible to researchers and AI agents.
- Use Claude and internal agent frameworks heavily in daily work, feeding learnings back to model-improvement and product teams as evaluations, datasets, and failure cases.
- Flexibly pick up analyses across projects as priorities shift, emphasizing breadth over a single deep specialty.
Minimum Qualifications
- PhD in computational biology, bioinformatics, genomics, biophysics, machine learning, computer science, or a related quantitative or biological field (or equivalent industry research experience).
- Track record of leading end-to-end computational biology research from question to result, with evidence of impact (e.g., publications, preprints, released datasets/tools, or research that changed a program's direction).
- Demonstrated breadth across multiple areas of computational biology.
- Proficient in one or more scientific computing programming languages; comfortable working on large datasets in Linux and cloud environments.
- Ability to take an ambiguous biological question, scope the analysis, and produce actionable results for experimentalists.
- Strong communication skills for conveying computational results to both biologists and ML researchers.
Preferred Qualifications
- Comfort navigating ambiguity and developing solutions in rapidly evolving research environments.
- Results-oriented with a bias towards flexibility and impact.
- Hands-on experience in experimental biology or track record of designing experiments alongside experimentalists.
- Experience building tools, pipelines, or agentic systems on top of LLMs, or training models on biological sequence data.
- Deep expertise in one or two areas of computational biology (e.g., structural biology, metagenomics, single-cell genomics, or protein design) on top of required breadth.
Skills
Computational Biology, Bioinformatics, Genomics, Structural Bioinformatics, Phylogenetic Analysis, Comparative Genomics, Biological Sequence Modeling, Python, Linux, Cloud Computing, LLMs, Claude, Machine Learning
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