Über diese Research Scientist, Life Sciences (Computational) Stelle bei Anthropic
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. This role combines deep computational biology expertise with frontier AI capabilities, positioning Anthropic at the forefront of AI-driven scientific discovery.
As one of the first computational members of this Life Sciences research group, you'll work on a high-impact team that operates at the intersection of computational and experimental biology. You'll bring broad computational biology experience to bear across the team's projects, driving discoveries from large-scale computational analysis of biological data through to results our experimental scientists can test, and moving flexibly between problems as the science demands. You'll have substantial access to Claude and you'll help establish how computational biology operates at Anthropic.
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 scientific understanding and biomedicine. If you're excited about using your computational expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you.
Key responsibilities
- Build, run, and maintain the analysis pipelines that back the team's experimental programs: sequence analysis at petabyte scale, structural bioinformatics, phylogenetic and comparative genomics, design and analysis of high-throughput functional screens, biological sequence modeling, etc.
- Partner directly with experimental biologists to design experiments that produce high-quality data, and turn results around fast enough to immediately inform the next experiment
- Draw on the literature and curated biological knowledge bases alongside primary data to generate and prioritize hypotheses for experimental follow-up
- Stand up and maintain the team's computational infrastructure: data ingestion, workflow orchestration, internal databases, and the interfaces that make all of it accessible to both researchers and AI agents
- Use Claude and our internal agent frameworks heavily in your own work, and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases
- Pick up analyses across projects as priorities shift; we're looking for breadth and flexibility over a single deep specialty
Minimum qualifications
- Have a PhD in computational biology, bioinformatics, genomics, biophysics, machine learning, computer science, or a related quantitative or biological field, or equivalent industry research experience
- Have a track record of computational biology research you have led end to end, from question to result, with evidence of impact (for example publications, preprints, released datasets or tools, or research that changed a program's direction)
- Have demonstrated breadth across multiple areas of computational biology
- Are proficient in one or more programming languages used in scientific computing and comfortable working on large datasets in Linux and cloud compute environments
- Can take an ambiguous biological question, scope the analysis, and produce a result an experimentalist can act on
- Communicate computational results clearly to both biologists and ML researchers
Preferred qualifications
- Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments
- Are results-oriented, with a bias towards flexibility and impact
- Hands-on experience in experimental biology, or a track record of designing experiments side by side with 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 (for example structural biology, metagenomics, single-cell genomics, or protein design) on top of the required breadth
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.
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 — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
