General Description: This role will contribute to AI-enabled ADME and translational modeling within the DMPK function, developing and applying predictive and mechanistic modeling approaches to support molecule optimization, candidate selection, and translational decision-making across discovery and preclinical development programs. Working at the intersection of DMPK, data science, and translational pharmacology, the successful candidate will integrate AI/ML, IVIVE, PK/PD, and PBPK methodologies to improve the prediction of pharmacokinetic behavior and enable data-driven decisions. The role requires strong cross-functional collaboration and the ability to translate complex analyses into clear scientific recommendations that advance project objectives. Education Required: PhD in pharmaceutical sciences, pharmacology, computational biology, bioinformatics, biostatistics, computational chemistry, artificial intelligence, machine learning, data science, engineering, or a related quantitative and life sciences discipline.