Paid internship for 3-6 months.
Responsibilities Run and benchmark open-source protein design methods on real Adaptyv targets, validated against experimental data from our wet lab. Design binders for internal R&D campaigns, and track experimental performance across success rate, hit rate, kinetics, and developability. Build computational tooling around the design pipeline: structure prediction, filtering, and ranking, to triage large design pools down to candidates for synthesis and characterization. Support the technical side of our open competitions and hackathons: drafting track briefs, supporting participants, judging submissions, and writing up results. Contribute open data, blog posts, designer spotlights, and method comparisons to Proteinbase.
Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.
