Sr. Scientist, Computational Chemistry

About the Role

Responsible for driving the execution of computational-driven methodologies to design optimized compounds with balanced properties (targets, DMPK, in‑vivo) in drug discovery programs. Provides impactful insights and collaboration across projects ranging from early lead identification to late-stage optimization of advanced projects. Acts as a subject‑matter expert in one or more molecular discovery approaches such as Structure‑Based Design & FEP, Virtual Screening, Quantum Chemistry, Machine Learning / Modern AI, etc.

Communicates and presents computationally derived results to discovery project teams to facilitate effective decision‑making while demonstrating an independent work style that is fully collaborative and team‑oriented.

On‑site role located in San Diego.

• Prior experience with independently driving drug discovery projects is highly desired.
• Domain knowledge of physical chemistry, computational chemistry, cheminformatics, protein modeling/molecular dynamics, molecular modeling, pharmacophore analyses, library design, virtual HTS, diversity/similarity analyses, scaffold hopping, protein‑ligand modeling, commercial docking tools, and molecular dynamics methods.
• Develops advanced machine learning/AI in‑silico models for DMPK/in‑vitro biology endpoints and enables more efficient MPO analyses and new compound designs.
• May have exposure to harnessing large datasets including public domain chemistry datasets and/or chemogenomic data.
• Demonstrates overall application of integrated approaches (e.g., ML predictions coupled with modeling of SBD/LBD) to progress compound design contextually in drug discovery, exhibiting innovative approaches that tweak commercial solutions.
• Independently drives drug discovery projects involving structure‑based design, including target protein flexibility considerations.
• Serves as an independent computational chemistry representative on project teams, working with minimal guidance while demonstrating clear impact on a chemical series evolution.
• Advances the company’s computational platform with expert knowledge, providing innovative ideas that contribute significantly to progressing compounds for multiple projects.
• Leads 1–2 advanced technology platforms, defining new computational methods in tandem with relevance to projects to augment Neurocrine’s platform.
• Engages stakeholders from multiple research functions to deliver and exchange key results.
• Drives and/or aligns with strategies emanating from project teams, department, and computational chemistry group.
• Provides training and/or supervision to junior staff as needed.
• Other duties as assigned.

• BS/BA in Chemistry with 5+ years of relevant experience, including familiarity with protein‑ligand modeling, molecular dynamics, and homology modeling (preferred).
• OR MS/MA in Chemistry with 3+ years of similar experience.
• OR PhD in Computational Chemistry or related field with some relevant experience.
• Postdoctoral experience in cheminformatics preferred.
• Experience in protein‑ligand docking & post‑docking processing, molecular dynamics, homology modeling, quantum chemistry, pharmacophore analyses, and diversity analyses.
• Comfortable with routine programming & scripting in Python, C++, and/or R.
• Working knowledge of computational technologies for early‑stage target assessment (e.g., druggability).
• Familiarity with commercial molecular modeling suites such as Schrödinger, CCG, or Open Eye.
• Demonstrates solid understanding of project/group goals and methods.
• Consistently recognizes anomalous and inconsistent results and interprets experimental outcomes.
• Able to explain the data process and implications of results.
• Strong knowledge and expertise in one or more scientific disciplines.
• Strong knowledge of scientific principles, methods, and techniques.
• Strong knowledge and demonstrated ability with laboratory equipment/tools.
• Team‑oriented mindset; may train lower‑level staff.
• Excellent computer skills.
• Strong communications, problem‑solving, and analytical thinking skills.
• Detail‑oriented while seeing the broader scientific impact on the team.
• Ability to meet multiple deadlines with high accuracy and…