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 (include, but are not limited to):- 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, analytical thinking skills
- Detail oriented yet can see broader picture of scientific impact on team
- Ability to meet multiple deadlines, with a high degree of accuracy and efficiency
- Strong project management skills
- A collaborative & team-oriented mindset is essential
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The annual base salary we reasonably expect to pay is $110,800.00-$151,000.00. 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.