Sr. Scientist, Computational Chemistry | Alabaster, AL

Biosciences is a neuroscience-focused, biomedical 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 Abb Vie 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. 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 Tensor Flow, Py Torch, 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.

Requirements and essential functions A collaborative & team-oriented mindset is essential Responsible for the communication and presentation of computationally derived results to the discovery project teams to facilitate effective decision-making. Familiarity with well-known commercial molecular modeling software suites is also desirable such as Schrodinger, CCG, or Open Eye.

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 (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. Comfortable with routine programming & scripting including Python, C++, and/or R.

Experience with Pipeline Pilot or Knime would be an asset. Linux administration is desirable but not essential. Exposure to harnessing large datasets including public domain datasets of chemistry related to various targets and/or chemogenomic nature would be an asset. Other duties as assigned BS degree in chemistry or related area with 4 years + relevant experience including utilizing any or all of the following Protein-ligand, modeling, Molecular Dynamics, and Homology Modeling MS degree in chemistry and 4 years of similar experience noted above OR Ph.

D. in computational chemistry or related field with 2+ years of related industry experience. #AD1Neurocrine 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. The annual base salary we reasonably expect to pay is $103,200.00-$149,700.00. Individual pay decisions depend on various factors, such as primary work location, complexity and responsibility of role, job duties/requirements, and relevant experience and skills.

In addition, this position offers an annual bonus with a target of 20% of the earned base salary and eligibility to participate in our equity based long term incentive program. Benefits offered include a retirement savings plan (with company match), paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage in accordance with the terms and conditions of the applicable plans.