Associate Director, QSP Modelling

About This Role

This Associate Director role focuses on Quantitative Systems Pharmacology (QSP) within the Drug Metabolism and Pharmacokinetics (DMPK) department. The successful candidate will develop and apply QSP models from early research through clinical development, integrating data and knowledge to understand physiological systems and disease mechanisms. The aim is to influence target prioritization, modality evaluation, and deliver transformative molecules into the clinic.

Responsibilities

• Build and utilize QSP models of biological, physiological, and pathophysiological processes to evaluate diseases, pathways, progression, drug candidates, and treatment modalities
• Work in close collaboration with biologists, clinicians, clinical pharmacologists, QSP and nonclinical modelers, and other partner line colleagues to inform research programs and improve understanding of disease mechanisms
• Serve as a disease-area QSP lead, possessing or developing expertise in disease pathophysiology, biomarkers, clinical endpoints, and key experimental methodologies and data
• Serve as QSP modeling and simulation point-of-contact on project teams to solve challenging problems in drug research; contribute to preclinical study design and mechanistic interpretation of data
• Develop and/or utilize state-of-the-art mathematical tools to gain insight into causal relationships between individual components of system-level and drug-level responses of drug-target-biomarker-disease-patient interaction
• Analyze and interpret complex data sets in the context of disease mechanisms and pathways
• Explore new opportunities to combine QSP with other analytical approaches and build synergies through collaboration with computational groups working in areas related to human genetics, functional genomics, and AI/ML
• Perform scientific rigor and biological suitability assessment of QSP models and methodologies through applying a context-driven verification and validation process (reviewing QSP model goals, assumptions, methodology, model code, model outputs, uncertainty quantification)

Requirements

• PhD in Applied Mathematics, Engineering, Pharmaceutical Sciences, Systems Biology, or related disciplines with experience in the application of mathematical and statistical methods
• 2 or more years of experience in Pharma Life Science Biomedical industry developing and applying QSP approaches to drug discovery or development programs
• Experience working with the theory, principles, statistical aspects of mathematical modeling and simulation, including numerical methods, parameter estimation/optimization, ordinary differential equations (ODEs), and how these can be applied in the development of complex models of biological pathways and systems
• Computational experience with one or more modeling and simulation packages or programming languages (e.g., MATLAB, SimBiology, Julia, Python, C/C++)