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Job Description
The Senior Scientist, AI-Enabled De Novo Antibody Discovery, Protein Therapeutics will help advance AI-enabled de novo antibody discovery through iterative design-build-test-learn cycles. This role combines antibody discovery, structural biology, and computational methods to translate target protein structure, biology, and therapeutic mechanism of action into epitope selection and end-to-end discovery campaign design. You will lead de novo binder design campaigns, bridge computational and experimental antibody discovery, and help establish lab-in-the-loop platforms that connect computational design, experimental screening, and iterative learning.
This position is based in Foster City, California, and is fully onsite.
As a Senior Scientist, AI-Enabled De Novo Antibody Discovery, Protein Therapeutics at Gilead, you will...
Key Responsibilities:
Lead de novo antibody discovery and optimization campaigns from target and epitope assessment through design, screening, iteration, and hit selection.
Develop integrated computational and experimental screening strategies for de novo designs, including candidate prioritization, library design, multiplexing, and recombinant and display-based approaches.
Critically evaluate experimental and predicted structural models to prioritize biologically relevant epitopes and guide discovery strategies.
Integrate computational, structural, binding, functional, and developability data to inform campaign iteration and binder advancement decisions.
Rapidly prototype computational workflows that address antibody discovery and optimization needs.
Collaborate with machine learning scientists to refine, scale, and implement broadly useful computational solutions.
Partner with data scientists, structural biologists, and high-throughput screening scientists to build scalable lab-in-the-loop capabilities for de novo antibody discovery and optimization.
Serve as a bridge between computational and experimental antibody discovery teams supporting project teams across Gilead therapeutic
areas.
Basic Qualifications:
Bachelor’s Degree and 8+ years of relevant experience
OR
Master’s Degree and 6+ years of relevant experience
OR
PhD or PharmD and 2+ years of relevant experience
Preferred Qualifications:
PhD in structural biology, protein engineering, biochemistry, biophysics, computational protein design, or a related discipline.
Industry experience in antibody discovery or engineering spanning target assessment through lead optimization.
Demonstrated ability to independently design, lead, and execute antibody discovery campaigns in a cross-functional environment.
Experience with conventional antibodies and VHHs.
Strong expertise in structural biology and protein structure-function relationships, including the evaluation of experimental and predicted antibody-target…