Postdoctoral Research Associate
Listed on 2026-02-06
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Research/Development
Research Scientist, Data Scientist, Clinical Research
Posting Information
Department School of Data Sci and Society - 397100
Posting Open Date 01/30/2026
Final date to receive applications 02/04/2026
Open Until Filled No
Position Type Postdoctoral Scholar
Position Title Postdoctoral Research Associate
Vacancy PDS
004767
Full-time/Part-time Full-Time Temporary
Hours per week 40
FTE 1
Work Location Chapel Hill, NC
Position Location North Carolina, US
Hiring Range $62,000 - $65,000, dependent on experience
Proposed Start Date 09/01/2026
Estimated Duration of Appointment 12 Months
Position InformationBe a Tar Heel! A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities and is among the top ten research universities in the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development.
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.
Summary
Dr. Jun Li’s lab ((Use the "Apply for this Job" box below).) at the University of North Carolina at Chapel Hill is recruiting postdoctoral researchers to join his interdisciplinary team. The lab focuses on integrative cancer omics, functional proteomics, and AI-driven bioinformatics tool development, with the overarching goal of advancing cancer treatment through data-driven translational research. Our work bridges data science and oncology by pursuing two main directions: (1) leveraging clinical and multi-omics data to generate hypotheses, uncover novel cancer vulnerabilities, and optimize therapeutic strategies, and (2) developing AI-powered analytical platforms to support patient-centered biomedical research.
Current projects involve building computational frameworks for multi-omics integration, modeling cancer vulnerabilities, designing tools for data interpretation and visualization, and/or training foundation models and large language models (LLMs) for diverse biomedical applications. Dr. Li has published over 70 peer-reviewed articles with more than 53,000 citations (H-index: 56), including first-author papers in Cancer Cell, Nature Cancer, Nature Methods, Nature Communications, and Science Advances, reflecting the lab’s strong track record in high-impact cancer research.
This position offers a dynamic and collaborative environment with ample opportunities for high-impact research, technical innovation, and professional growth.
A Ph.D. in Computational Biology, Bioinformatics, Computer Science, Cancer Biology, or a related field.
Required Qualifications , Competencies, And Experience- Proficiency in programming (e.g., Python, R, or similar).
- Experience with large-scale omics data analysis.
- Excellent written and verbal communication skills.
- Solid understanding of cancer biology and omics technology (e.g., genomics, proteomics, and/or metabolomics).
- Strong publication record in relevant fields.
- Proven ability to develop bioinformatics tools or AI/ML models.
- Experience in integrating multi-omics data from tumors and preclinical models.
- Familiarity with training or fine-tuning large-scale models (e.g.,…
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