Senior Scientist II, ML Expert - Pharmacology (Drug Discovery)

Responsibilities

• Consult with project team to establish quantitative targets for driving optimization.
• Identify suitable models to predict small molecule binding affinities for protein targets, and to predict pharmacological properties (PK parameters, etc.).
• Build predictive models for each project endpoint, and carefully benchmarking to evaluate performance and domain of applicability for each model.
• Decisively identify the model that should be used for each project team query molecule, using data-driven approaches that take account of model uncertainty and heteroscedasticity.
• Clearly communicate to the project team the rationale for model selection and why the selected models are best suited for the task at hand.
• Deploy models to ensure accessibility for the project team, facilitating collaborative ideation and optimization.

Requirements

• Bachelor's Degree or equivalent education and typically 12+ years of industry experience, Master's Degree or equivalent education and typically 10+ years of industry experience, PhD and typically 4+ years of industry experience.
• Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning and Cheminformatics.
• Expertise in AI/ML-enabled molecular generation, pose prediction, affinity prediction and/or prediction of pharmacological properties (e.g. PK).
• Strong programming skills in Python and experience with data science stack including numpy, pandas, scikit-learn, and other related scientific libraries.
• Ability to implement, debug, and maintain computational tools in common programming languages (Python, etc...) and proficiency with cloud computing capabilities.
• Familiarity with modern deep learning architectures including GNN, CNN, RNN, Transformer, GCNN and MPNN, and machine learning paradigms such as generative models, GAN, and active learning.
• Strong analytical and problem-solving skills with demonstrated ability to think critically and creatively, and provide solutions both individually and collaboratively with internal experts.
• Excellent ability to communicate clearly and concisely with colleagues and collaborators including an ability to explain complex ideas to non-specialists.
• Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
• This job is eligible to participate in our long-term incentive programs.
• AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
• US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
• US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
• https://www.abbvie.com/join-us/reasonable-accommodations.html

Benefits

Additional Information

Purpose This position brings an opportunity to make innovative contributions that will define how AbbVie leverages AI-enabled drug discovery across our small molecule portfolio. The key responsibilities of this position are to identify, develop, optimize, validate, and deploy innovative machine learning approaches to guide molecular optimization. This role will collaborate closely with project teams comprising medicinal chemists, structural biologists, biochemists, cell biologists, and other computational chemistry / chemoinformatics experts.

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