Manager/Associate Director - Predictive Sciences, Asia Translational Medicine

GSK•Upper Providence, PA

1d•Hybrid

About The Position

We are seeking a highly motivated translational scientist to join the Predictive Sciences group within Asia Translational Medicine (ATM), where quantitative modeling, clinical pharmacology, biomarkers, and translational data science are integrated to enable model-informed research and development. This role offers a unique opportunity to shape global clinical development by leveraging Asia's rapidly evolving biomedical innovation ecosystem, diverse patient populations, and growing translational research capabilities to generate actionable insights with enterprise-wide impact. In this role, you will partner with regional and global, multidisciplinary clinical and translational teams to develop and apply cutting-edge quantitative approaches that inform clinical development strategies and deepen our understanding of causal disease biology and therapeutic response. Working across multiple therapeutic areas and advanced therapeutic modalities - including therapeutic proteins, antibodies, and nucleic acids (particularly, siRNA and antisense oligonucleotides) - you will integrate mechanistic modeling, biomarkers, translational -omics, and clinical trial data to enable model-informed drug development. You will also help advance state-of-art predictive modeling methodologies and computational capabilities that strengthen quantitative translational science across the portfolio.

Requirements

PhD, PharmD, MD, or equivalent doctoral degree in Pharmaceutical Sciences, Quantitative and/or Clinical Pharmacology, Bioengineering, Mathematics, Medicine, or a related quantitative discipline.
Experience in mechanistic modeling approaches, including PK/PD, PBPK, and/or QSP, applied to drug development.
Experience with integrating quantitative modeling with clinical pharmacology, biomarkers, relevant clinical endpoints, and biological/disease mechanisms to inform translational and clinical development.
Fluency in English (written and oral) is required.

Nice To Haves

Experience with use of AI/ML, virtual population, or digital twin approaches for executing in silico clinical trial simulation is advantageous.
Excellent communication and collaboration skills.
Experience working in multidisciplinary drug development teams (for Associate Director-level).
Experience within immunology, hepatology, respiratory, renal, oncology, or related therapeutic areas.
Experience applying predictive modeling approaches to biologics, oligonucleotides, or other advanced therapeutic modalities.
Track record of scientific publication, conference presentations, and application of model-informed drug development in research and/or development projects.

Responsibilities

Serve as the Predictive Sciences representative on multidisciplinary translational medicine teams, developing and applying quantitative strategies that contribute to biomarker strategy and inform clinical development and model-informed decision making.
Develop and apply mechanistic modeling approaches - including PK/PD, PBPK/PD, QSP, and AI/ML-enabled analytics - to integrate clinical and translational data, characterize human pharmacology (including ethnopharmacology), evaluate alternative trial designs, and forecast the probability of technical success for different dosing regimens, combination strategies, patient populations, and regional standards of care.
Generate quantitative evidence that informs critical project and portfolio decisions, including candidate progression, clinical development strategy, and investment prioritization.
Partner closely with Clinical Pharmacology, Biomarkers, Bioanalytical Sciences, Clinical Development, and other partnering functions to address complex scientific questions and advance translational hypotheses.
Communicate quantitative strategies and modeling results to project teams, governance committees, regulatory agencies, and external scientific audiences with clarity and scientific rigor.
Advance Predictive Sciences through the development and application of innovative modeling methodologies, computational technologies, and reusable quantitative frameworks with impact across therapeutic areas and development programs.