Role: Scientist, Computational Protein Design
Adimab is the leading technology provider for therapeutic antibody drug discovery, focusing solely on our partnerships without pursuing an internal product pipeline. Since 2009, we have partnered with over 140 pharmaceutical and biotechnology companies, generating more than 650 therapeutic programs, of which more than 85 have entered clinical trials.
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.
Skills Required
- PhD in Biophysics, Biochemistry, Structural Biology, Computational Biology, or related field
- 2-4 years post-PhD experience in computational protein or binder design
- Strong foundation in analysis of structural and energetic factors driving protein-protein interactions
- Proficiency with structure prediction and generative design tools (e.g., RFAntibody, BindCraft, Protenix)
- Crystallography or cryo-EM experience
- 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
What We Do
Adimab is the most successful antibody discovery company in the industry, with 600+ discovery campaigns and 80+ clinical programs created with more than 130 partners. Our unique, yeast-based platform is a comprehensive and effective tool for the discovery and optimization of fully human monoclonal and bispecific antibodies. Our partners range from some of the biggest pharma to biotech companies at all stages to leading academic institutions. We're committed to staying at the cutting edge of protein-based therapeutic discovery to enable the highest quality IgGs, multispecifics, CARs and other modalities to allow our partners to have the most successful therapeutic programs possible.








