The role
From AbbVie's own posting.
The Molecular Profiling and Drug Delivery (MPDD) function within the Synthetic Molecule CMC organization is accountable for a broad range of deliverables across multiple stages of drug discovery and development. From virtual screening, lead generation, and lead optimization through candidate selection, MPDD scientists use state-of-the-art automation and computational tools, supported by expertise in biopharmaceutics, drug delivery, and solid-state chemistry, to collaboratively design and advance candidates with a higher probability of success into development and to inform clinical drug-delivery strategy. From candidate selection through clinical proof of concept and product launch, MPDD scientists work on cross-functional teams to identify the commercial solid form of the active pharmaceutical ingredient (API) and establish structure–property–performance correlations that help deliver robust commercial processes and align control strategies across drug substance and drug product. 
 
Computational chemists within AbbVie’s MPDD organization partner across Development Sciences and Discovery Sciences in three key focus areas: molecular design and profiling, chemical transitions, and materials design across synthetic modalities. Their work supports the design and advancement of compounds, materials, and formulations with optimal developability properties from lead optimization through commercial development, aligned with the broader goal of advancing first-in-class and best-in-class clinical candidates. The team develops hierarchical modeling approaches that integrate physics-based atomistic methods, including molecular dynamics and quantum mechanics, with machine learning, artificial intelligence, and hybrid physics-informed AI/ML models across hardware platforms for precision in predictions. In close collaboration with medicinal chemists, data scientists, materials scientists, formulation scientists, engineers, and molecular modelers, the team embeds these tools into screening funnels across medicinal chemistry design cycles and preclinical and clinical drug-substance and drug-product development, while maintaining a strong partnership ecosystem to source and leverage external innovation. 
 
Job Description 
AbbVie’s MPDD organization is seeking a highly motivated, talented, and creative scientific leader with deep expertise in computational chemistry for a Principal Scientist II position. This individual will help shape and advance the organization’s computational sciences vision in alignment with AbbVie’s broader R&D priorities and AI strategy. In this role, the successful candidate will collaboratively guide the identification, development, piloting, implementation, and eventual democratization of stage-appropriate computational models that leverage advanced computational techniques to enable the design and optimization of drug candidates across synthetic modalities. The ideal candidate will bring a strong record of project impact, capability development, and external partnership building across the mid- to late-stage discovery process, with expertise in quantum mechanics, atomistic molecular simulations, including molecular dynamics, and AI/machine learning. Prior experience mentoring early- and mid-career scientists in matrixed and/or direct-reporting relationships is also expected. 
Responsibilities 
Partner with project teams across Discovery and Early Development to establish quantitative objectives for lead optimization and de-risking from candidate nomination through candidate selection. 
Provide scientific leadership in applying computational chemistry approaches to molecular design and profiling and, more broadly, to chemical transitions and materials design across synthetic modalities. 
Guide computational chemistry team members in designing and executing benchmarking studies to evaluate model performance, applicability, and limitations. 
Clearly communicate the rationale for selecting specific computational models and workflows, including their relevance to project objectives and stage-appropriate applications. 
Lead the development, implementation, and continuous improvement of a cohesive portfolio of internal computational models and workflows that address AbbVie’s small-molecule and synthetic-modality needs. 
Apply physics-based computational methods, including quantum mechanics and atomistic molecular simulations, as well as machine learning, artificial intelligence, and hybrid physics-informed AI/ML approaches to support drug discovery and development. 
Collaborate with medicinal chemists, data scientists, materials scientists, formulation scientists, engineers, molecular modelers, and other cross-functional partners to integrate computational tools into design and screening workflows. 
Proactively provide expert advice, technical guidance, and shared knowledge to direct reports, peers, project teams, and senior leaders. 
Identify emerging scientific trends from internal and external sources and incorporate relevant opportunities into functional objectives and longer-term computational sciences strategies. 
Lead or support the identification, development, piloting, implementation, and democratization of computational capabilities across appropriate discovery and development workflows. 
Present program updates, research strategies, and scientific recommendations to functional and cross-functional leaders, project teams, and external partners. 
Maintain awareness of emerging literature, technologies, and scientific advances in computational chemistry, data science, and AI/ML, and translate relevant developments into actionable research opportunities. 
Prepare and deliver concise scientific presentations, publications, conference abstracts, and other scientific disclosures within and outside AbbVie. 
Build and maintain strong relationships with external collaborators and partners to source, evaluate, and leverage external innovation. 
Participate in internal and external initiatives and working groups to influence scientific thinking, approaches, and standards in computational medicinal chemistry. 
Ensure compliance with all applicable AbbVie policies and procedures. 
 
 
Qualifications 
Bachelor’s degree or equivalent education in chemistry, computational chemistry, pharmaceutical sciences, chemical engineering, computer science, or a related scientific field, with typically 16+ years of related work experience; Master’s degree or equivalent education, with typically 14+ years of related work experience; or a PhD in chemistry, computational chemistry, pharmaceutical sciences, chemical engineering, computer science, or a related field, with typically 8+ years of related work experience. 
Extensive knowledge and experience applying computational chemistry and data science approaches to medicinal chemistry, drug discovery, and molecular optimization. 
Extensive knowledge and experience with modern computational methods, including quantum mechanics, molecular dynamics, atomistic molecular simulations, machine learning, artificial intelligence, and/or hybrid physics-informed AI/ML approaches. 
Demonstrated experience developing, evaluating, and applying computational models and workflows across multiple stages of the drug discovery and development process. 
Experience establishing model performance benchmarks, defining domains of applicability, and communicating model limitations and appropriate use to multidisciplinary project teams. 
Demonstrated ability to translate complex computational concepts and scientific results into clear, actionable recommendations for technical and nontechnical audiences. 
Experience leading multiple complex research programs, initiatives, or capability-development activities in a matrixed and/or direct-reporting envi