Adaptyv
Intern, Protein Design
1mo ago
EuropeTraineeRemoteprotein designai modelslab instrumentsexperimental data
Internship role focused on running and benchmarking open-source protein design methods validated against experimental data, designing binders, and tracking experimental performance in a biotech AI-driven lab.
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.
Requirements
- 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.
- Duration: 3-6 months. Paid.
- Location: Remote, or on-site in Lausanne. Lausanne is preferred if you want lab access and the full design-build-test-learn exposure.
Other
- 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. 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.
- We are reviewing applicants on a rolling basis. Please include a link to a GitHub repository, competition submission, blog post, or other concrete work demonstrating your approach to protein design.
- We are reviewing applicants on a rolling basis.