Anthropic’s Life Sciences team seeks a medicinal chemist to design and synthesize small molecules, integrate AI-generated hypotheses, and drive experimental programs end-to-end in San Francisco. The role combines chemistry expertise, synthetic planning, and data analysis to advance life‑science research.
Research Scientist, Life Sciences (Chemistry) na Anthropic
Presencial - San Francisco, CA
Ver mais vagas na AnthropicSalary
USD 300,000 - 320,000
Requirements
Skills
- PhD in chemistry
- Demonstrated medicinal chemistry experience, including SAR-driven design and optimization of small molecules, with recent, sustained hands-on synthetic work
- Comfort navigating ambiguity and defining problems in a rapidly evolving research environment
- Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills
- 5+ years of medicinal chemistry experience beyond the PhD
- Track record of advancing programs from hit identification through lead optimization
- Experience directing synthetic chemistry activities at contract research organizations
- Computational chemistry, cheminformatics, or coding skills, for example Python with RDKit or pandas for data analysis and automation
- Experience using AI or ML tools in the life sciences
- Publications and/or patents demonstrating scientific impact
Responsibilities
- Design multi-step synthetic routes for small molecules and oversee their execution end to end, including route selection, reaction optimization, purification strategy, and interpretation of full characterization data (NMR, LC-MS, HPLC)
- Coordinate synthesis and biological evaluation with external contract research organizations and academic partners
- Evaluate AI-designed molecules and AI-proposed synthetic routes, drive them to experimental readout, and feed results back to research teams
- Apply medicinal chemistry principles, including SAR analysis and physicochemical property optimization, to compound design and prioritization
- Ensure experimental data across programs is high quality and well documented, including procedures, spectra, and failure modes
- Communicate findings clearly to chemistry, AI research, and life sciences audiences
Technologies
PythonRDKitpandasAI toolsML tools
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