Senior Research Investigator/Associate Director, Clinical QSP Team

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

We are seeking experienced scientists with expertise in mechanistic modeling to support drug development across therapeutic areas. The ideal candidate will support early and late-stage clinical drug development across therapeutic areas by leveraging Quantitative Systems Pharmacology (QSP) modeling to de-risk and optimize development from First-in-Human (FIH) through Proof-of-Concept (PoC) and beyond. This includes informing dose selection for Phase 1 through Phase 3 studies across various drug modalities and combination regimens, elucidating mechanisms of action, extrapolating efficacy to new or adjacent patient populations, evaluating competitive differentiation, and supporting internal decision-making and regulatory submissions. Experience in virtual population development and qualification, particularly using AI- and ML-based approaches, is highly desirable. Prior industry experience and a strong record of collaboration with discovery, translational, and clinical development teams are strongly preferred. Familiarity with immunology and relevant experimental methods is considered an asset.

Our team has a strong foundation in developing, calibrating, and applying mechanistic models to drive decisions across preclinical and clinical development. We work in a blended environment with scientists from QSP, PBPK and clinical PMx to create and implement aligned and impactful modeling strategies. 

Key Responsibilities:
Lead and collaborate with cross-functional project teams to develop and apply QSP models to address critical drug development questions
•    Independently design, implement, and interpret mechanistic models to support clinical study design, dose selection, and regulatory strategy
•    Engage external collaborators to accelerate modeling efforts in high-priority disease areas
•    Integrate preclinical and clinical data to inform model development and refinement
•    Coordinate with PBPK and CMx groups to implement and tailor virtual population workflows and standardized analytical approaches
•    Actively engage with stakeholders across R&D, including Research & Early Development (R&ED) and Global Drug Development (GDD), to support model-informed decision-making
•    Align modeling deliverables with clinical pharmacology, model-informed drug development (MIDD), and overall clinical development plans
•    Contribute to departmental initiatives, including setting modeling best practices and advancing internal capabilities
•    Stay current with advances in systems pharmacology, modeling & simulation, and relevant therapeutic biology
•    Represent QSP internally and externally as a scientific leader and subject matter expert
•    Maintain an active track record of scientific publications and presentations in QSP or related fields
•    Foster strong collaborations with colleagues across Translational Medicine and Clinical Pharmacology and other functions

Qualifications:
•    Ph.D. in Engineering, Mathematics, Bioinformatics, Pharmacometrics, Systems Biology/Pharmacology, or a related field
•    5+ years of relevant modeling and simulation experience in pharmaceutical R&D or consulting; postdoctoral experience may be considered
•    Deep understanding of quantitative modeling principles and methodologies, with demonstrated application to biological and pharmacological systems
•    Strong foundation in pharmacokinetics and pharmacodynamics
•    Ability to rapidly learn new areas of biology and integrate that knowledge into mechanistic models
•    Effective communication skills to engage scientific and cross-functional audiences, both internally and externally
•    Familiarity with the latest advancements in systems pharmacology and virtua