Scientist II, Computational Chemistry

neurocrine; San Diego (CA); On-site; USD 130,000 - 195,000; Full time

Job summary

Neurocrine Biosciences seeks a computational chemistry expert to drive machine learning and in-silico modeling for DMPK and in-vitro endpoints. You will own predictive platforms, provide insights to discovery teams, and lead advanced computational methods to accelerate lead optimization.

The role requires strong chemistry and cheminformatics knowledge, along with experience in molecular modeling, scripting (Python/C++/R), and collaboration across research functions.

Qualifications

• BS/BA in Chemistry with 5+ years of relevant experience in molecular modeling or Cheminformatics.
• MS/MA in Chemistry with 3+ years of similar experience in computational chemistry preferred.
• PhD in Computational Chemistry or related field; postdoctoral Cheminformatics experience preferred.

Responsibilities

• Develop advanced ML/AI in-silico models for DMPK and in-vitro endpoints.
• Own predictive platforms with regular updates and maintenance.
• Advise on modelling studies to advance projects in drug discovery.
• Advance computational platform through expert knowledge and novel methods.
• Collaborate with multiple Research functions to share results and insights.
• Explain data and implications of results to project teams.

Skills

Machine Learning

Python

C++

R

Analytical thinking

Education

BS/BA in Chemistry

MS/MA in Chemistry

PhD in Computational Chemistry

Tools

Schrodinger

OpenEye

CCG

Python scripting

Job description

Who We Are:

Neurocrine Biosciences is a leading biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering, developing and commercializing life‑changing treatments for patients with under‑addressed neurological, psychiatric, endocrine and immunological disorders. The company's diverse portfolio includes FDA‑approved treatments for tardive dyskinesia, chorea associated with Huntington’s disease, classic congenital adrenal hyperplasia, hyperphagia in Prader-Willi syndrome, endometriosis* and uterine fibroids*, as well as a robust pipeline including multiple compounds in mid- to late‑phase clinical development across our core therapeutic areas. For more than three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders, because you deserve brave science. For more information, visit neurocrine.com , and follow the company on LinkedIn , X , Facebook and YouTube . ( *in collaboration with AbbVie )

About the Role:

Responsible for driving the execution of computational driven methodologies to help design optimized compounds with balanced properties (targets, DMPK, in-vivo) in drug discovery programs. Provides impactful insights and collaboration on projects ranging from early lead identification to the late-stage optimization of advanced projects. Serves as a subject matter expert in 1 or more molecular discovery approaches such as: machine learning, modern AI, modeling predictions, etc. Responsible for the communication and presentation of computationally derived results to the discovery project teams to facilitate effective decision- making.

Your Contributions

• Develops advanced Machine Learning/AI in-silico models for numerous DMPK/in-vitro Biology endpoints, for front-loading projects with appropriate predictive information, to enable more efficient MPO analyses
• Takes ownership of predictive platform and provides maintenance including regular updates and analysis
• Provides strong contribution for modelling studies to the advancement of projects
• Advances the company's computational platform with expert knowledge providing innovative ideas to make significant contributions, establishing the groups cutting edge technology that is aligned with team's strategy to progress compounds forward for multiple projects
• Leads 1-2 advanced technology platforms, defining new computational methods, in tandem with self-interest and relevance to projects, to help augment Neurocrine's Computational Chemistry platform for Drug Discovery
• Engages stakeholders from multiple Research functions to deliver and/or exchange key results
• Effectively contributes to the assessment of early-stage projects to help determine its entry into portfolio
• 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

Requirements

• BS/BA degree in Chemistry AND 5+ years of relevant experience, including familiarity utilizing any or all of the following: Protein-Ligand modeling, Molecular Dynamics, Homology Modeling is preferred OR
• MS/MA degree in Chemistry AND 3+ years of similar experience noted above OR
• PhD in Computational Chemistry or related field AND some relevant experience. Postdoctoral experience in Cheminformatics preferred
• Strong knowledge of any or all of the following: Chemistry, Computational Chemistry, Cheminformatics, Protein Modeling, Molecular Modeling as employed for the optimization of lead compounds is preferred
• Experience in one or more of the following Molecular Modeling domains is highly desirable: Protein Ligand docking & post-docking processing, Molecular Dynamics, Homology Modeling, Quantum Chemistry, Pharmacophore Analyses and Diversity Analyses
• Comfortable with routine programming & scripting including python, C++ and/or R
• Working knowledge about computational technologies for the assessment of early-stage targets (ex: druggability)
• Familiarity with well-known commercial molecular modeling software suites is also desirable such as Schrodinger, CCG or Open Eye
• Demonstrates solid level of understanding project / group goals and methods
• Consistently recognizes anomalous and inconsistent results and interprets experimental outcomes
• Able to explain the process behind the data and implications of the results
• Strong knowledge of one or more scientific disciplines, becoming expert in one discipline
• Strong knowledge of scientific principles, methods and techniques
• Strong knowledge and demonstrated ability working with a variety of laboratory equipment/tools
• Ability to work as part of a team; may train lower levels
• Excellent computer skills
• Strong communications, problem-solving, analytica