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) in drug discovery programs, that could range from early lead identification to late-stage optimization phase. Will be a member of multi-disciplinary drug discovery teams of medicinal chemists, DMPK, structural biologists and pharmacologists, where opportunities to impact will abound. Experience with Molecular Modeling domains is required, as applied to compound design and optimization such as Pharmacophore Analyses, Library Design, virtual HTS, Diversity/Similarity Analyses, Scaffold Hopping. A demonstrated success with an overall application of several integrated approaches (ex: ML derived predictions, Modeling SBD/ LBD) to progressing compound design contextual in drug discovery, is highly desirable and will serve as a strong bonus to consideration. Publications, posters or documented examples would be helpful. Preference also given to candidates with previous roles in biotech/pharma companies and capable of independently driving forward Drug Discovery projects involving Structure Based Design including, but not limited to, target protein flexibility considerations. Exposure to harnessing large datasets including public domain datasets of chemistry related to various targets and/or chemogenomic nature would be an asset. Knowledge about computational technologies for the assessment of early-stage targets (ex: druggability) is helpful but not essential. Familiarity with well-known commercial molecular modeling software suites is also desirable such as Schrodinger, CCG or Open Eye. _ Please note this will be a 6 month contract