Postdoctoral Scientist (Computational & Structural Bioinformatics)

Gilead Sciences • Foster City, CA

11d

About The Position

Join a pioneering team at the forefront of computational and structural biology, driving innovation to transform therapeutic discovery. We are seeking an exceptional Postdoctoral Scientist to lead research focused on predicting and optimizing protein–protein interactions using cutting-edge approaches that combine physics-based modeling, machine learning, and experimental validation, advancing the design of next-generation proteins and antibodies. This position is a joint appointment between Research Data Sciences and Protein Therapeutics, providing a un ique opportunit y for cross-functional collaboration and exposure to diverse expertise. As a Postdoctoral Scientist, you will have the freedom to design and lead an independent research project, publish in high-impact journals, and work alongside world-class scientists across computational and experimental disciplines. Your contributions will directly shape the future of biologics and antibody therapeutics.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Biophysics, or related fields .
• At least one first- author publication in a peer-reviewed journal.
• Strong Python programming skills with extensive experience using scientific libraries (e.g., NumPy, SciPy, pandas) and deep learning frameworks including PyTorch and TensorFlow.
• Expertise in protein modeling tools ( AlphaFold, RFDiffusion , Rosetta, PyMOL , etc )
• Proficiency in Linux environments and deploying workflows on HPC clusters .
• Excellent problem-solving and communication skills.

Nice To Haves

• Experience with graph neural networks, diffusion models, or generative frameworks for antibody design and optimization.
• Knowledge of enhanced sampling techniques ( M etadynamics , U mbrella sampling).
• Understanding binding thermodynamics and free energy calculations.
• Experience and/or famil iarity with approaches for affinity validation and screening in the lab ( e.g. high throughput recombinant protein production, ELISA, SPR/BLI, flow cytometry, display technologies, NGS) - training provided as needed.

Responsibilities

• Develop advanced computational workflows for protein modeling, structural analysis, and molecular simulations.
• Apply machine learning and physics-based approaches to predict and optimize protein-protein interactions.
• Analyze large-scale biological datasets to uncover insights that guide experimental design.
• V alidate computational predictions and generate critical training datasets in the lab .
• Optimize automated cloud-based pipelines for large-scale predic tions and data processing.
• Publish and present your findings at top-tier conferences and journals.

Benefits

• paid time off
• company-sponsored medical, dental, vision, and life insurance plans

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees