Computational Biologist Principal Research Scientist II

What you'll do

• Develop and deliver a computational immunogenicity strategy aligned with Development Sciences priorities.
• Lead the development and deployment of predictive models for preclinical and clinical immunogenicity risk assessment.
• Apply protein language models, generative AI, and physics-informed modeling to identify immunogenicity drivers and biomarkers.
• Integrate multi-omics, transcriptomic, and clinical datasets to characterize immune responses to biologics.
• Build and manage scalable data pipelines and tools for scientific knowledge mining and hypothesis generation.
• Translate complex scientific analyses into clear recommendations for project teams, governance bodies, and senior leadership.
• Manage, mentor, and develop a team of computational scientists and protein engineers.

What we're looking for

• Ph.D. in a related scientific field with experience, or a Master’s degree with experience.
• Demonstrated expertise in computational protein science, biologics discovery, AI/ML, and predictive modeling.
• Proven ability to define scientific strategy, lead multidisciplinary programs, and manage scientific teams.
• Proficiency in Python and machine-learning frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
• Experience with HLA binding, T-cell epitope prediction, single-cell analysis, knowledge graphs, RAG systems, or biomedical language models.
• Experience handling large experimental, biological, clinical, structural, or multi-omics datasets and maintaining reproducible data pipelines.
• Demonstrated understanding of physical principles governing protein structure, folding, binding, and molecular recognition.
• Experience with immunogenicity risk assessment, ADA data interpretation, and FDA/EMA guidance (preferred).