Role: Scientist, Computational Protein Design
Role Overview The role is on Adimab's computational biology team in Mountain View, CA. Data-driven approaches have been central to the development of the Adimab platform, and the team is actively utilizing and developing modern de novo protein design and generative AI methods to extend its capabilities. You will serve as the computational lead for protein design campaigns, embedded within a world-class team of modeling and wet-bench scientists, with direct access to Adimab's industry-leading experimental capabilities to drive the design-build-test cycle.
Responsibilities - Take end-to-end ownership of computational protein design campaigns - from design generation through wet-lab collaboration, analysis of experimental data, and optimization of the design-build-test cycle. Applications span de novo epitope-targeted IgG, VHH, and minibinder design, as well as protein solubilization and stabilization.
- Partner with wet-lab teams to design experiments that generate custom training data for affinity, epitope, and specificity prediction models. Train and rigorously benchmark resulting models against internal and external baselines.
- Build and maintain the computational infrastructure supporting both protein design campaigns and model development, including reproducible pipelines and integration of computational outputs with wet-lab data.
- Track developments in computational protein design and ML; evaluate relevance to Adimab's platform and identify opportunities for integration.
- Serve as a resource for wet-lab scientists on AI/ML capabilities and best practices, helping antibody and protein engineering teams apply computational design methods.
Needed Upon Hire - PhD in Biophysics, Biochemistry, Structural Biology, Computational Biology, or a related field.
- 2-4 years of post-PhD experience specifically in computational protein or binder design.
- Strong foundation in the analysis of structural and energetic factors driving protein-protein interactions.
- Proficiency with structure prediction and generative design tools such as RFAntibody, BindCraft, and Protenix. Crystallography or cryo-EM experience is a plus.
- Strong Python skills and experience building reproducible analysis and modeling pipelines.
- Proven track record of publication or patent contribution in applied ML for proteins or computational design.
Come join us! Our integrated antibody discovery and engineering platform provides unprecedented speed from antigen to purified, full-length human IgGs with exquisite specificity and biophysical behavior. We offer fundamental advantages by delivering diverse panels of antibodies that meet the most demanding standards for affinity, epitope specificity, species cross-reactivity, and developability. We enable our partners to rapidly expand their biologics pipelines through a broad spectrum of technology access arrangements.
As a profitable privately-held biotech company, we take a long-term view on value creation and make substantial investments in technology development, research, and our people. We offer individually tailored compensation packages comprised of a competitive salary, meaningful equity, a 2:1 401(k) match, and comprehensive health care benefits.
