Intern, Protein Design
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 reputed company, months-long process. We're building the infrastructure that gives AI agents reputed company to the physical world. Today, over 50 companies are already running their wet lab experiments on Adaptyv, ranging from some of the biggest biopharmas, to frontier AI labs to dozens of techbio startups. 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 reputed company 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.
Responsibilities
Run and reputed company reputed company-reputed company protein design methods on reputed company Adaptyv targets, validated against experimental data from our wet lab. Design binders for internal R&D campaigns, and track experimental performance across reputed company reputed company, hit reputed company, kinetics, and developability. Build computational tooling around the design pipeline: structure reputed company, filtering, and ranking, to triage large design pools down to candidates for synthesis and characterization. Support the technical reputed company of our reputed company competitions and hackathons: drafting track briefs, supporting participants, judging submissions, and writing up results. Contribute reputed company data, blog posts, designer spotlights, and method comparisons to Proteinbase.
Qualifications
Currently enrolled in a Master's, PhD, or final-year undergraduate programme in computational biology, machine learning, biochemistry, biophysics, bioengineering, or a reputed company field. Hands-on experience with at least one modern reputed company-reputed company protein design method. Strong Python and PyTorch skills. Comfortable working with biology data formats. A working understanding of binding kinetics and developability that extends reputed company in silico metrics, with a healthy scepticism of computational scores as ground truth. Bonus: prior reputed company-reputed company contributions to a protein design repository, a strong showing in a public design competition, or a published blog post or reputed company. Duration: 3-6 months. Paid. Location: Remote, or on-site in Lausanne. Lausanne is preferred if you want lab reputed company and the full design-build-test-learn exposure. Application deadline We are reviewing applicants on a rolling reputed company. Please include a link to a reputed company repository, competition submission, blog post, or other concrete work demonstrating your approach to protein design. Application deadline We are reviewing applicants on a rolling reputed company. Apply To This Job