At Neurocrine Biosciences, we pride ourselves on having a strong, inclusive, and positive culture based on our shared purpose and values. We know what it takes to be great, and we are as passionate about our people as we are about our purpose - to relieve suffering for people with great needs, but few options.
What We Do:Neurocrine Biosciences is a neuroscience-focused, biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs, but few options. We are dedicated to discovering and developing life-changing treatments for patients with under-addressed neurological, endocrine and psychiatric disorders. The company’s diverse portfolio includes FDA-approved treatments for tardive dyskinesia, Parkinson’s disease, endometriosis* and uterine fibroids*, as well as clinical programs in multiple therapeutic areas. For 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. *in collaboration with AbbVie
About the Role:Neurocrine is expanding our R&D chemistry capabilities. In this exciting new role, you will be instrumental in the success of our growing computational chemistry team. The successful candidate will be responsible for the execution of computational-driven methodologies to help design optimized compounds with balanced properties (targets, DMPK, in-vivo). Your industry knowledge will include expertise in machine learning tools, and analytics, along with expertise with structure-based design methods to support drug discovery projects in the industry, for our growing pipeline._
**Please note this will be a 6 month contract**Your Contributions (include, but are not limited to):Projects could range from early lead identification to the late-stage optimization of advanced projects. In particular, you will be able to join and potentially lead the development of an in-silico modeling platform within the Chemistry Department. As an active contributing member of multi-disciplinary drug discovery projects comprised of Medicinal Chemists, Biologists, DMPK & toxicologists there will be enormous opportunities to impact projects, as well as ample collaboration opportunities to share and learn from similar ML-derived predictive modeling efforts in other Neurocrine’s R&D functions
Expertise with structure-based design methods to support drug discovery projects in the industry
Experience in machine learning approaches in their application to compound design and drug discovery is essential, which would include modern AI such as Deep Learning, Generative Modeling and Knowledge Graphs, and/or classical methods of Random Forest, KPLS, SVM, etc. Knowledge about ML environments and libraries such as TensorFlow, PyTorch, RDKit, Scikit-learn, etc., is highly desirable as well as a deep understanding of validation metrics behind ML models. Additional suggested modern contextual topics may include meaningful connection of model predictions back to chemical structures, Polypharmacology (multiple targets with similar compounds), Protein Dynamics/ Ligand Binding, Data visualization metrics, and more
Contributes to the Computational Chemistry group’s efforts in implementing computational chemistry and/or cheminformatics methods for expediting the Design-Make-Test-Analyze discovery cycle
Generates productive hypotheses from Protein-ligand docking, for project teams that leads to successful compound optimization in subsequent design cycles
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
Facilitate the medicinal chemists design new compounds with desirable optimizable properties that are predicted using cutting-edge computational technologies integrating structural, chemical and biological data
Employs computational platform to make significant contribution to rationalizing experimental results, SAR evolution, and generating impactful ideas that are aligned with team’s strategy to progress compounds forward in projects
Plays a lead role in identifying and/or developing/refining new computational methods, in tandem with self-interest and relevance to projects, to help augment Neurocrine’s Computational Chemistry platform for Drug Discovery
Participates in a multidisciplinary team committed to the continuous improvement of the lead optimization process as well as the expeditious identification of development compounds.
Engages stakeholders from multiple Research functions to deliver and/or exchange key results
May contribute to the assessment of early-stage projects to help determine its entry into portfolio
Keeps abreast of developments of related interest through literature and advises project teams and/or computational chemistry group of innovation that could be harnessed into improving our platform
Aligned with strategies emanating from project teams, department and computational chemistry group
Conducive to sharing knowledge, practices, and work details, as needed, with teams and receptive to incorporating ideas from teams for continuous enrichment to best practices
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: Machine Learning/AI based predictive modeling, Cheminformatics, Protein-Ligand 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
Recognizes fundamental anomalies in data points and identifies issues in experiments / processes
Begins to understand how to think outside of the technical process and consider the impact decisions will have on the broader scientific goals
Strong knowledge of scientific discipline
Good knowledge of scientific principles, methods and techniques
Good knowledge and demonstrated ability working with a variety of laboratory equipment/tools
Strong computer skills
Good problem-solving, analytical thinking skills
Detail oriented
Ability to meet deadlines
Excellent communication skills with the ability to collaborate with cross-functional scientists
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Neurocrine Biosciences is an EEO/AA/Disability/Vets employer.
We are committed to building a diverse, equitable, and inclusive workplace, and we recognize there are a variety of ways to meet our requirements. We are looking for the best candidate for the job and encourage you to apply even if your experience or qualifications don’t line up to exactly what we have outlined in the job description.