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

Position: Translational Pharmacology, Omics, & AI - Assistant/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 research faculty position at the Assistant or Associate Professor level. We seek an innovative and collaborative scientist with expertise in quantitative pharmacology or toxicology, with complementary expertise in exposomics, proteomics, metabolomics, artificial intelligence/machine learning (AI/ML), quantitative modeling, systems biology, computational sciences, or related disciplines.exposomics,

artificial intelligence (AI), machine learning (ML), systems biology, quantitative modeling, computational sciences, or related disciplines.  The successful candidate will develop an independent, externally funded research program focused on understanding how drugs, environmental exposures, nutrition, microbiome-derived factors, and other components of the exposome influence child development, disease susceptibility, therapeutic responses, and lifelong health outcomes. Research programs integrating human-relevant New Approach Methodologies (NAMs), including organoids, microphysiological systems, and multi-omics data with AI/ML-enabled predictive frameworks are particularly encouraged.  

TCP is internationally recognized for leadership in pediatric clinical and translational pharmacology, pharmacometrics, multi-omics, physiologically based pharmacokinetic (PBPK) modeling, quantitative systems pharmacology (QSP), environmental health sciences, model-informed precision dosing (MIPD), and model-informed drug development (MIDD). Faculty benefit from extensive collaborations across Cincinnati Children's and the University of Cincinnati in clinical, translational, and computational sciences.

We seek faculty who will complement existing strengths through innovative experimental, computational, or integrated research programs while contributing to multidisciplinary collaborations that improve child health.  
** Key Responsibilities
** Research* Develop and lead an independent, externally funded research program.
* Conduct innovative research in one or more of the following areas:  + Pediatric pharmacology and developmental pharmacology  + Toxicology, exposomics, and environmental health sciences  + Multi-omics integration, biomarker discovery, and precision medicine  + AI/ML-enabled biomedical research  + PBPK, PopPK, PK/PD, QSP, systems toxicology, and mechanistic modeling  + Translation of NAM-derived data to human and pediatric populations  + Hybrid mechanistic-AI approaches for predicting exposure, disease progression, and therapeutic outcomes
* Develop frameworks that connect experimental models, omics data, and clinical outcomes.
* Establish collaborations that accelerate translational applications and therapeutic innovation.  
** Collaboration, Education, and Service
*** Build collaborations within TCP and across Cincinnati Children's and the University of Cincinnati.
* Work closely with clinicians, quantitative scientists, computational biologists, and AI researchers.
* Mentor graduate students, postdoctoral fellows, trainees, and junior faculty.
* Participate in institutional, national, and international scientific activities.
* Contribute to strategic initiatives that strengthen TCP's leadership in translational pharmacology, toxicology, exposomics, and precision medicine.  
** Required Qualifications
*** PhD, PharmD/PhD, MD/PhD, or equivalent doctoral degree in a relevant discipline.
* Demonstrated expertise in quantitative pharmacology or toxicology, with complementary expertise in exposomics, proteomics, metabolomics, artificial intelligence/machine learning (AI/ML), quantitative modeling, systems biology, computational sciences, or related disciplines.
* Strong publication record and potential to secure extramural funding.
* Experience working with biological, clinical, environmental, pharmacological, or multi-omics datasets.
* Excellent communication skills and commitment to collaborative science.  
** Preferred Qualifications
*** Expertise in AI/ML, PBPK, PopPK, QSP, PK/PD, systems toxicology, or mechanistic modeling.
* Experience with organoids, organ-on-chip systems, microphysiological systems, or other NAMs.
* Interest in pediatric health, developmental biology, environmental health sciences, rare diseases, or precision medicine.
* Experience integrating omics, imaging, or clinical data into predictive models.
* Familiarity with advanced computational methods, including cloud…