research
Posted 1 weeks agoScientist, Antibody Developability
at Adaptyvbio
Lausanne, United StatesOn-site
Requirements
- 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.
- You'll develop the assays hands-on, work with lab automation to scale them, and work with the software and ML teams to model the data and make it useful for protein designers.
- - Work with the software and ML teams to structure developability data and connect it to computational developability prediction.
- experience assessing antibody developability — you know the assay panel cold and have used it to triage real antibody campaigns. - Applied industry experience.
- This is the core requirement. - Strong grasp of what makes a biologic developable — the link between early biophysical signals and downstream manufacturability and stability. - Builder who moves fast.
- You collaborate naturally with automation engineers and with software/ML people, and you're excited about closing the loop between wet-lab data and predictive models. - Data fluency (scripting, working with structured datasets) is a strong plus.
Additional details
- But they can't run the experiments themselves - that's still a manual, months-long process.
- This is a rare chance to help advance some of the most important work happening in biotech today.
- Aggregation, thermostability, self-association, polyreactivity, solubility, viscosity, and chemical liabilities: you'll build the experimental stack that flags these early, and make it something customers can order as a product.
- These assays exist today as a scattered, bespoke collection.
- Your job is to turn them into one coherent, automated, high-throughput developability assessment — and to connect the experimental data to in-silico prediction so the lab and the models reinforce each other.