Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Machine Learning @ 2
Python @ 2
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic's Life Sciences team is building a research group focused on fundamental biological discoveries by combining artificial intelligence with hands-on biological research. This role operates at the intersection of computational and experimental biology and involves using Claude and internal agent frameworks for experimental planning, protocol development, and data interpretation.
Responsibilities
- Design, execute, and iterate on experimental programs involving molecular biology, biochemistry, protein and nucleic acid characterization, high-throughput functional screens, and assay development.
- Partner with computational biologists to design experiments that produce high-quality, analysis-ready data and rapidly feed results into subsequent analysis.
- Generate and prioritize hypotheses using experimental judgment, scientific literature, curated biological knowledge bases, and computational predictions.
- Use Claude and internal agent frameworks for experimental planning, protocol development, and data interpretation.
- Feed experimental learnings back to model-improvement and product teams through evaluations, datasets, and concrete failure cases.
- Help establish Anthropic as a leader in biology research while developing product intuition through direct engagement with laboratory science.
Requirements
- Ph.D. in a biological science, such as molecular biology, biochemistry, bioengineering, or computational biology, or a related field.
- Track record of bridging biological domain knowledge with computational approaches to solve real scientific problems.
- Basic proficiency in Python and familiarity with machine learning development practices.
- Ability to navigate ambiguity and develop solutions in rapidly evolving research environments.
- Ability to work independently while collaborating effectively with cross-functional teams.
- Results-oriented approach with flexibility and a focus on impact.
- Ability to work in a fast-paced research environment while balancing rigorous scientific standards with rapid iteration.
- Published research or practical experience in scientific AI applications is preferred.
- Familiarity with modern machine learning techniques and model training methodologies is preferred.
- Familiarity with biological databases, including UniProt, GenBank, and PDB, and computational biology tools is preferred.
Compensation
- Annual salary: $300,000–$320,000 USD.
Work Arrangement and Logistics
- Location-based hybrid policy: Staff are expected to work from an Anthropic office at least 25% of the time, although some roles may require more office time.
- Anthropic sponsors visas and makes reasonable efforts to support visa applications, although sponsorship is not guaranteed for every role or candidate.
- Minimum education listed in the logistics section: Bachelor's degree or an equivalent combination of education, training, and experience.
- Required field of study: A field relevant to the role, demonstrated through coursework, training, or professional experience.
- Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration spaces.
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