Postdoc Research Fellow - Dr. Cao Lab

Please see Special Instructions for more details. Posting Information Department Posting Open Date Posting Open Date 08/22/2025 Application Deadline Open Until Filled Yes Position Type Position Title Position Title Postdoc Research Fellow - Dr. Cao Lab Vacancy ID Vacancy ID PDS004630 Full-time/Part-time Full-time/Part-time Full-Time Temporary Hours per week 40 FTE

FTE 1

Work Location Position Location Position Location North Carolina, US Hiring Range Hiring Range Dependent on experience and qualifications. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our overall commitment to research excellence. Across many disciplines, postdocs contribute to the intellectual vitality of the University. They provide innovative ideas and perspectives, foster a stimulating research environment and advance knowledge within their fields. Postdocs are crucial members of our scientific research workforce, contributors to our research outputs and an important reason why Carolina is one of the leading public research institutions in the country. 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. Chapel Hill regularly ranks as one of the best college towns and best places to live in the United States, a reputation guided by the diverse social, cultural, recreation and professional opportunities that span the campus and community. The UNC Eshelman School of Pharmacy ( is one of six health science schools (Pharmacy, Nursing, Dentistry, Social Work, Public Health, Medicine) at the University of North Carolina at Chapel Hill and is one of the oldest health science academic programs at Chapel Hill. The School teaches approximately 600 PharmD students and 145 graduate students. The School has built a reputation for its continued pursuit of excellence, rigorous education and training programs, cutting-edge multidisciplinary research, progressive pharmacy practices, efficient business operations, and its outstanding faculty, staff, and students. The School was named the number one School of Pharmacy in the U.S. by the U.S. News and World Report. The School has experienced unprecedented growth and success and continues to strategically position itself for sustained impact, as articulated in the School’s Strategic Plan ( Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders and innovators to solve the world’s most pressing health care challenges. We are Advancing Medicine for Life through innovation and collaboration in pharmacy practice, education, research, and public service. Position Summary About the Group: 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:

1. Drug Pharmacokinetics (PK) and Clinical Relevance – Investigating how pharmacokinetic features relate to patient characteristics, drug efficacy, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data.
2. Modeling for Regulatory Science – Leveraging drug development and regulatory datasets to build models and generate evidence that can inform regulatory decision-making and accelerate the development of safe and effective therapeutics.

Position Overview: We are seeking multiple highly motivated Postdoctoral Research Fellow with expertise in systems pharmacology, machine learning, and/or data science to join our interdisciplinary team. The successful candidate will work at the intersection of drug development, regulatory science, and advanced computational modeling. This position will involve 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. This position will have a great opportunity to interact with top experts in the field to directly address drug development issues. 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. If you experience any problems accessing the system or have questions about the application process, please contact the University’s Office of Postdoctoral Affairs at View phone number on click.appcast.io or send an email to View email address on click.appcast.io . Please note: The Office of Postdoctoral Affairs will not be able to provide specific updates regarding position or application status. 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. Optional and Required Documents Curriculum Vitae / Resume Cover Letter List of References Optional Documents Supplemental Questions Required fields are indicated with an asterisk (*). * Please select the response below that describes your level of education. Some high school High School/GED Associate's Degree Bachelor's Degree Master's Degree Doctoral Degree, JD or Other Terminal Degree * Briefly describe your experience with designing and implementing computational approaches combining mechanistic modeling and machine learning to study drug PK, efficacy, and safety. (Open Ended Question) #J-18808-Ljbffr UNC-Chapel Hill