Principal Research Scientist II, Molecular Profiling and Drug Delivery (MPDD)
AbbVie
August 18, 2026
Remote friendly (North Chicago, IL)
United States
$141,500 - $268,500 USD yearly
Clinical Research and Development
Responsibilities:
- Partner with Discovery and Early Development teams to set quantitative objectives for lead optimization and de-risking from candidate nomination through selection.
- Provide scientific leadership applying computational chemistry to molecular design/profiling, chemical transitions, and materials design across synthetic modalities.
- Guide benchmarking studies to evaluate model performance, applicability, and limitations.
- Select and communicate rationales for computational models/workflows aligned to project objectives and stage-appropriate use.
- Lead development/implementation/continuous improvement of internal computational models and workflows for small molecules and synthetic modalities.
- Apply physics-based methods (quantum mechanics, molecular dynamics, atomistic simulations) plus ML/AI/hybrid physics-informed AI/ML.
- Collaborate cross-functionally to integrate computational tools into design and screening workflows.
- Provide expert advice and technical guidance; identify trends and translate them into actionable strategies.
- Lead/support identification, piloting, implementation, and “democratization” of computational capabilities.
- Present strategies/recommendations; maintain awareness of literature/tech; publish/present/disclose findings.
- Build external partnerships; participate in working groups; ensure compliance with applicable AbbVie policies.
Qualifications:
- BS (16+ yrs) / MS (14+ yrs) / PhD (8+ yrs) in chemistry, computational chemistry, pharmaceutical sciences, chemical engineering, computer science, or related field.
- Extensive experience with computational chemistry and data science for medicinal chemistry/drug discovery/molecular optimization.
- Expertise in quantum mechanics, molecular dynamics/atomistic simulations, ML/AI and/or hybrid physics-informed AI/ML.
- Experience developing/evaluating computational models across discovery & development stages; establish benchmarks and domains of applicability.
- Ability to translate complex results into actionable recommendations for technical and nontechnical audiences.
- Experience leading complex programs in matrix/direct-report environments; mentoring early- and mid-career scientists.
- Strong analytical/problem-solving, organization, and communication; publications/presentations/patents preferred.
Benefits (if applicable):
- Paid time off; medical/dental/vision insurance; 401(k) (eligible employees); long-term incentive program participation.
- Partner with Discovery and Early Development teams to set quantitative objectives for lead optimization and de-risking from candidate nomination through selection.
- Provide scientific leadership applying computational chemistry to molecular design/profiling, chemical transitions, and materials design across synthetic modalities.
- Guide benchmarking studies to evaluate model performance, applicability, and limitations.
- Select and communicate rationales for computational models/workflows aligned to project objectives and stage-appropriate use.
- Lead development/implementation/continuous improvement of internal computational models and workflows for small molecules and synthetic modalities.
- Apply physics-based methods (quantum mechanics, molecular dynamics, atomistic simulations) plus ML/AI/hybrid physics-informed AI/ML.
- Collaborate cross-functionally to integrate computational tools into design and screening workflows.
- Provide expert advice and technical guidance; identify trends and translate them into actionable strategies.
- Lead/support identification, piloting, implementation, and “democratization” of computational capabilities.
- Present strategies/recommendations; maintain awareness of literature/tech; publish/present/disclose findings.
- Build external partnerships; participate in working groups; ensure compliance with applicable AbbVie policies.
Qualifications:
- BS (16+ yrs) / MS (14+ yrs) / PhD (8+ yrs) in chemistry, computational chemistry, pharmaceutical sciences, chemical engineering, computer science, or related field.
- Extensive experience with computational chemistry and data science for medicinal chemistry/drug discovery/molecular optimization.
- Expertise in quantum mechanics, molecular dynamics/atomistic simulations, ML/AI and/or hybrid physics-informed AI/ML.
- Experience developing/evaluating computational models across discovery & development stages; establish benchmarks and domains of applicability.
- Ability to translate complex results into actionable recommendations for technical and nontechnical audiences.
- Experience leading complex programs in matrix/direct-report environments; mentoring early- and mid-career scientists.
- Strong analytical/problem-solving, organization, and communication; publications/presentations/patents preferred.
Benefits (if applicable):
- Paid time off; medical/dental/vision insurance; 401(k) (eligible employees); long-term incentive program participation.