below marketmost similar roles pay hereabove market
This role pays less than
59%
of similar roles. Most pay
$177,587–$256,850
— the blue band above.
At the midpoint, this role pays about
$205k
versus about
$217k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
145 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 140 roles with salary data.
The Principal Research Scientist II, Computational Sciences, MPDD joins the Molecular Profiling and Drug Delivery function within the Synthetic Molecule CMC organization. This role provides scientific leadership to guide the identification, development, and democratization of computational models that optimize drug candidates across synthetic modalities. You will lead the development of a cohesive portfolio of internal workflows to support molecular design, chemical transitions, and materials design from lead optimization through commercial development. Key responsibilities include benchmarking model performance, mentoring scientists, and collaborating with cross-functional partners to integrate tools into screening funnels. You will utilize physics-based atomistic methods, including quantum mechanics and molecular dynamics, alongside machine learning, artificial intelligence, and hybrid physics-informed AI/ML models. This work addresses the technical challenge of establishing structure–property–performance correlations to ensure robust commercial processes.
What does a Research Scientist earn?
Median $216250 from 45 postings across 16 companies.
Apply physics-based methods like quantum mechanics and molecular dynamics alongside AI/ML to support drug discovery.
Lead the development and implementation of internal computational models and workflows for small-molecule and synthetic modalities.
Partner with project teams to establish quantitative objectives for lead optimization and de-risking during candidate selection.
Guide team members in designing benchmarking studies to evaluate model performance, applicability, and limitations.
Integrate computational tools into design and screening workflows by collaborating with medicinal chemists, data scientists, and engineers.
Identify emerging scientific trends and translate them into actionable research opportunities and long-term computational strategies.
Mentor early- and mid-career scientists while providing technical guidance to peers and senior leadership.
Build and maintain relationships with external partners to source and leverage external innovation.
What we're looking for
Bachelor’s degree with 16+ years of experience, Master’s with 14+ years, or PhD with 8+ years in a related scientific field.
Extensive experience applying computational chemistry and data science approaches to medicinal chemistry, drug discovery, and molecular optimization.
Extensive experience with quantum mechanics, molecular dynamics, atomistic molecular simulations, machine learning, artificial intelligence, and hybrid physics-informed AI/ML.
Demonstrated experience developing, evaluating, and applying computational models and workflows across multiple stages of drug discovery and development.
Experience establishing model performance benchmarks, defining domains of applicability, and communicating model limitations to multidisciplinary teams.
Demonstrated experience mentoring early- and mid-career scientists and leading complex research programs in matrixed or direct-reporting environments.
Strong ability to translate complex computational concepts into actionable recommendations for both technical and nontechnical audiences.
A record of scientific contributions through publications, conference presentations, abstracts, or patents (preferred).
Machine Learning
Deep Learning
Python
Cheminformatics
Generative AI
Molecular Generation
Retrosynthetic Analysis
Pose Prediction
Computational Chemistry
Drug Discovery
Chemical Engineering