Intern, Protein Design

United StatesHybrid

Responsibilities

- 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.

Adaptyv is building an automated lab thats let 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.
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.
We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.
QUALIFICATIONS - Currently enrolled in a Master's, PhD, or final-year undergraduate programme in computational biology, machine learning, biochemistry, biophysics, bioengineering, or a related field. - Hands-on
experience with at least one modern open-source protein design method. - Strong Python and PyTorch skills.
Comfortable working with biology data formats. - A working understanding of binding kinetics and developability that extends beyond in silico metrics, with a healthy scepticism of computational scores as ground truth. - Bonus: prior open-source contributions to a protein design repository, a strong showing in a public design competition, or a published blog post or paper.
Please include a link to a GitHub repository, competition submission, blog post, or other concrete work demonstrating your approach to protein design.