Principal Computational Scientist, Discovery Chemistry

Lead the development and implementation of advanced computational methods (structure-based, physics-based) for target and peptide modeling and optimization. Apply ML models to predict peptide properties such as solubility, permeability, stability, immunogenicity, and potency. Design, develop, and deploy a unified computational platform for peptide therapeutic discovery, building complex workflows to enable design and optimization of peptide modalities. Collaborate with AI for Drug Discovery teams to apply AI/ML techniques (protein-ligand co-folding, generative and active learning) to advance drug discovery. Build robust data infrastructure and automated pipelines for processing large datasets from NGS and integrate crystallography, biomolecular NMR, cryo-EM, and biophysics data. Work with multidisciplinary teams, including wet-lab scientists, to ensure data-driven workflows. Required strong communication skills and ability to convey complex concepts to diverse audiences. Preferred experience with non-canonical amino acids and computational software (MOE, Schrodinger, OpenEye, Rosetta); experience with AI/ML in peptide design; publications in leading journals. Relocation benefits available. Salary range based on California location: $144,900–$269,100; discretionary annual bonus may apply.