Research Scientist, Life Sciences (Experimental Biology)

Anthropic · AI Research & Engineering

支持签证Anthropic H-1B 获批 76 次 (FY2025)英国签证担保名单$300k–$320k/年San Francisco, CA发布 2026-07-08
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Visa sponsorship:  We do sponsor visas!

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职位描述 Job description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the team

Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery.

About the role

We're seeking an exceptional Research Scientist to join the team. As a founding member of Life Sciences, you'll work in a high-impact group that operates at the intersection of computational and experimental biology. You'll help establish Anthropic as a leader in biology research while developing product intuition through direct engagement with the challenges and opportunities of laboratory science.

Key responsibilities

Design, execute, and iterate on the experimental programs at the core of the team's research: molecular biology, biochemistry, protein and nucleic acid characterization, high-throughput functional screens, and the assay development that makes new questions answerable

Partner directly with computational biologists to design experiments that produce high-quality, analysis-ready data, and feed results back fast enough to immediately inform the next round of analysis

Generate and prioritize hypotheses by combining your experimental judgment with the literature, curated biological knowledge bases, and the team's computational predictions

Use Claude and our internal agent frameworks heavily in your own work — for experimental planning, protocol development, and data interpretation — and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases

Minimum qualifications

Have a Ph.D. in a biological science (molecular biology, biochemistry, bioengineering, computational biology) or a related field

Have a track record of bridging biological domain knowledge with computational approaches to solve real scientific problems

Have basic proficiency in Python and are familiar with ML development practices

Preferred qualifications

Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments

Can work independently while maintaining strong collaboration with cross-functional teams

Are results-oriented, with a bias towards flexibility and impact

Thrive in a fast-paced research environment where you balance rigorous scientific standards with rapid iteration

Published research or practical experience in scientific AI applications

Familiarity with modern machine learning techniques and model training methodologies

Familiarity with biological databases (UniProt, GenBank, PDB) and computational biology tools

This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for human health and scientific understanding. If you're excited about using your expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$300,000 — $320,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit  anthropic.com/careers  directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact —

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