Translational Pharmacology, Omics, & AI - Assistant/Associate Professor - Tenure Track

Primary Location Location S Department Transl and Clin Pharmacology Shift Day (United States of America) Schedule Full time Weekly Hours 40 FTE 1 Employee Status Regular Assistant or Associate Professor (Tenure-Track) The Division of Translational and Clinical Pharmacology (TCP) at Cincinnati Children's Hospital Medical Center (CCHMC) invites applications for a Tenure-Track faculty position at the Assistant or Associate Professor level. We seek an innovative and collaborative computational scientist with expertise in quantitative pharmacology, systems pharmacology, artificial intelligence/machine learning (AI/ML) or bioinformatics. Complementary expertise in exposomics, proteomics, metabolomics, multi-omics integration, mechanistic modeling, or related quantitative disciplines is highly desirable. The successful candidate will develop an independent, externally funded research program leveraging large-scale biological, clinical, environmental, and/or multi-omics datasets to understand how drugs, environmental exposures, nutrition, microbiome-derived factors, and genetic variation influence pediatric disease, therapeutic response, and lifelong health outcomes. Particular emphasis will be placed on developing computational frameworks that integrate proteomic, metabolomic, exposomic, genomic, and clinical data to identify disease mechanisms, discover biomarkers, predict therapeutic response, enable drug repurposing, and accelerate treatment development for pediatric and rare diseases. Research programs that integrate exposomics, proteomics, metabolomics, human-relevant New Approach Methodologies (NAMs), patient-derived organoids, microphysiological systems, and real-world clinical data with AI/ML-enabled predictive frameworks are particularly encouraged. Applications focused on rare diseases, precision therapeutics, drug repurposing, biomarker discovery, disease progression modeling, digital twins, or model-informed precision dosing are of special interest. Required Qualifications * PhD, MD/PhD, PharmD/PhD, or equivalent in computational biology, bioinformatics, biomedical data science, pharmacometrics, systems pharmacology, toxicology, pharmacology, engineering, computer science, or a related discipline. * Demonstrated expertise in computational and quantitative approaches applied to biomedical research. * Experience analyzing and integrating large-scale biological, environmental, clinical, proteomic, metabolomic, exposomic, genomic, or other multi-omics datasets. * Strong publication record and demonstrated potential for independent extramural funding. * Commitment to collaborative and team-based translational science. Preferred Qualifications * Expertise in AI/ML, deep learning, generative AI, foundation models, causal inference, graph learning, or advanced statistical methods. * Experience integrating exposomics, proteomics, metabolomics, genomics, imaging, wearable sensor, or clinical datasets. * Expertise in PBPK, PopPK, PK/PD, QSP, systems biology, or mechanistic modeling. * Interest in rare diseases, pediatric therapeutics, precision medicine, environmental health, or drug repurposing. * Experience developing computational tools or predictive models for biomarker identification, disease progression, or therapeutic optimization. * Experience working with cloud computing, high-performance computing, or large biomedical dat