Postdoc Research Fellow - Dr. Cao Lab

Postdoc Research Fellow – Dr. Cao Lab University of North Carolina at Chapel Hill, Eshelman School of Pharmacy Position Summary Our research group is dedicated to developing innovative datasets and modeling approaches to support drug development and regulatory evaluation. We focus on two major research areas: Drug Pharmacokinetics (PK) and Clinical Relevance – Investigating how pharmacokinetic features relate to patient characteristics, drug efficacy, and safety profiles, and predicting these relationships using machine learning based on drug‑specific information, patient demographics, and clinical trial data. Modeling for Regulatory Science – Leveraging drug development and regulatory datasets to build models and generate evidence that informs regulatory decision‑making and accelerates the development of safe and effective therapeutics. We are seeking multiple highly motivated Postdoctoral Research Fellows with expertise in systems pharmacology, machine learning, and/or data science. The successful candidate will work at the intersection of drug development, regulatory science, and advanced computational modeling, integrating mechanistic modeling and machine learning methods to analyze and predict drug properties, patient responses, and benefit‑risk profiles using real‑world and regulatory datasets. The role offers opportunities to collaborate with top experts in the field. Minimum Education and Experience Requirements PhD in Biostatistics, Bioinformatics, Data Science, Pharmaceutical Sciences, Computer Science, Regulatory Science, or related fields. Required Qualifications, Competencies, and Experience Strong publication record in relevant disciplines. Demonstrated expertise in computational modeling, data analysis, and statistical/machine learning methods. Excellent communication and scientific writing skills. Experience in mechanistic pharmacokinetic/pharmacodynamic (PK/PD) modeling or systems pharmacology is highly desirable. Familiarity with regulatory science or clinical trial data is a plus. Preferred Qualifications, Competencies, and Experience Strong publication record in relevant disciplines. Demonstrated expertise in computational modeling, data analysis, and statistical/machine learning methods. Excellent communication and scientific writing skills. Experience in mechanistic pharmacokinetic/pharmacodynamic (PK/PD) modeling or systems pharmacology is highly desirable. Familiarity with regulatory science or clinical trial data is a plus. Benefits UNC‑Chapel Hill offers postdocs comprehensive medical and vision coverage, paid leave, and benefits and services that support professional development and a healthy work/life balance. Equal Opportunity Employer Statement The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities. #J-18808-Ljbffr