Principal Scientist, Computational Sciences - Protein Structure Prediction and Design

About The Role

Experienced, creative, collaborative scientist for Biotherapeutics Computational Design. Build and deploy ML and structure-based methods to accelerate biologics discovery (antibodies, multispecifics, ADCs, novel scaffolds) and scale an agentic antibody design platform.

• Develop and scale antibody design capabilities from prototype to application.
• Advance agentic antibody design into robust, reusable preclinical workflows.
• Build and apply models for protein structure modeling, binder design, affinity/specificity prediction, and develop ability prediction (internal/external datasets).
• Deliver production‑ready computational pipelines emphasizing reproducibility, benchmarking, and maintainable well‑documented code.
• Partner with computational and wet‑lab teams; prioritize capabilities and communicate insights to technical/non‑technical audiences.

• PhD in structural bioinformatics/computational biology/CS/engineering/physics or related + 4+ years relevant industry/academic experience.
• Modern ML expertise (e.g., transformers; diffusion/flow generative models) and strong classical ML foundations.
• Experience developing/evaluating predictive models (assessment, benchmarking, experimental design).
• Hands‑on protein modeling (structure prediction + generative protein design).
• Experience with agentic AI frameworks for research automation.
• Strong Python; reproducible research and high‑quality scientific software.
• Independent problem‑solving; clear cross‑disciplinary communication.

• Physics‑based modeling (e.g., MD, free energy perturbation) or closed‑loop optimization (e.g., Bayesian optimization, active learning).
• Background in biochemistry/protein engineering.

• Starting ranges:
  Brisbane/CA (US $166,770–$202,086);
  Cambridge (US $166,770–$202,086);
  San Diego/CA (US $156,890–$190,117).
• Health coverage; wellbeing programs; 401(k), disability, life/insurance;
  Paid Time Off (flexible/annual vacation/holidays by location).

Apply even if your experience doesn’t perfectly match.