Scientist II, Computational Chemistry

Role: Lead the development and application of machine learning and AI models in drug discovery to optimize compound properties related to DMPK and in-vitro biology endpoints. The position involves advancing computational platforms, modeling studies, and integrating innovative methods in molecular discovery. Responsibilities include maintaining predictive models, contributing to project assessments, and collaborating across research teams to inform decision-making. The role also entails leading 1-2 advanced computational platforms, providing training or supervision to junior staff, and driving strategic alignment within the department. Requirements: BS/BA in Chemistry with 5+ years, MS/MA with 3+ years, or PhD in Computational Chemistry or related field; experience with protein-ligand modeling, molecular dynamics, homology modeling, and proficiency in programming languages such as Python, C++, or R. Desirable skills include familiarity with commercial modeling software (e.g., Schrödinger, CCG, OpenEye) and druggability assessment tools. High-value biopharma specifics: focus on neuroscience-related targets, early to late-stage compound optimization, and cross-functional stakeholder engagement. The position is based at Neurocrine Biosciences with a competitive salary range ($110,800 - $151,000), bonus potential, and benefits, with location and travel details not specified.