Senior Principal Research Scientist, Computational Drug Discovery HitGen​/LeadGen Team Lead

Senior Principal Research Scientist, Computational Drug Discovery Hit Gen/Lead Gen Team Lead

• Full-time
• Salary Min: 160500
• Salary Max: 305000
• Workday Global Grade: 21
• Compensation: USD 160,500 - USD 305,000 - yearly

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on Linked In, Facebook , Instagram , X and You Tube.

Purpose

This position brings an opportunity to make innovative contributions that will define how Abb Vie leverages AI-enabled drug discovery across our small molecule portfolio. Reports to Head of Computational Drug Discovery (CDD) and will lead the computational Hit Gen/Lead Gen (HGLG) team. Will implement and enable close collaboration between members of the HGLG team and partners in the Target Enabling Technologies (TET) and Global Medicinal Chemistry (GMEC) teams.

Must possess a strong expertise in modern medicinal chemistry, including a deep understanding of modern computational and experimental strategies and property-based drug design. The ideal candidate will have a strong and established background from having worked on a broad range of diverse early-stage campaigns, and an established external footprint and network. Past experience will have included mentorship of early/mid-career scientists in matrixed and/or direct reporting relationships.

Responsibilities

• Consult with project team to establish desirable project-relevant hit/lead criteria, and assign an HGLG member to the project team that can execute these goals for accelerated identification of suitable chemical matter
• Guide HGLG members in benchmarking experiments to evaluate models’ performance and domain of applicability
• Clearly communicate to project teams the rationale for selecting specific approaches and how they suit project needs
• Lead development of a cohesive collection of cutting-edge methods and workflows, to comprehensively address Abb Vie’s small molecule portfolio needs (methods for predicting binding affinities of diverse chemo types, for predicting pharmacological properties for diverse chemo types (PK parameters, etc.), and for rapidly sampling both enumerated and AI-generated chemical spaces)
• Work closely with the TET and GMEC leadership teams to identify and address gaps where computational predictions are needed
• Advance scientific expertise within the HGLG team and collaborate with cross-disciplinary teams from CDD and Information Research to advance programs and ensure computational capabilities are best implemented across programs
• Proactively demonstrate leadership by providing expert advice and shared knowledge with direct reports, peers, and senior management
• Identify and integrate emerging scientific trends from internal and external sources into functional objectives
• Present program updates and research strategies to functional and non-functional leaders as well as potential and existing partners
• Maintain awareness of emerging literature and science in the field and author scientific disclosures/publications
• Maintain scientific presence outside Abb Vie with appropriate publication and conference abstract submissions highlighting innovative learnings in computational medicinal chemistry

Qualifications

• Bachelor’s Degree or equivalent education in science-related field with extensive (typically > 18 years) of related work;
  Master’s Degree or equivalent education with extensive (typically > 16 years) of related work;
  PhD in Science or related field with typically 10+ years of related work experience
• Highly organized and self-directed, experience leading multiple complex simultaneous research programs or initiatives
• Extensive knowledge and experience in applying data science approaches for drug discovery
• Extensive knowledge and experience in modern computational approaches for drug discovery
• Excellent written and…