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Post-Doc Research Associate

University of North Carolina - Chapel Hill
$55,000 - $65,000
United States, North Carolina, Chapel Hill
104 Airport Dr (Show on map)
Nov 19, 2024
Posting Information
Posting Details


Department Biostatistics - 462001
Posting Open Date 10/15/2024
Application Deadline 12/13/2024
Open Until Filled No
Position Type Postdoctoral Scholar
Position Title Post-Doc Research Associate
Vacancy ID PDS004357
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 $55,000 - $65,000
Proposed Start Date 01/01/2025
Estimated Duration of Appointment 12 Months
Position Information


Be 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 is 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.
Primary Purpose of Organizational Unit
The Department of Biostatistics ( BIOS) is internationally recognized as a leader in Biostatistics research and training. It is one of eight departments in the Gillings School of Global Public Health whose mission is to improve the health and wellbeing of the population. This mission is accomplished through the interaction of teaching, research and service. The department is one of the largest, most complex departments on campus. For FY19, Biostatistics, was 4th among all departments and centers across campus in research funding at UNC Chapel Hill and currently has almost 300 employees. The Department operates a $46 million sponsored research budget (FY19), a 1.7-million-dollar state budget, a 1.0-million-dollar F&A budget and spends roughly 3.0 million in trust funds annually. The Department has 55 EHRA and EHRA Non-Faculty members, 74 permanent staff members and 162 temporary employees. The Department has 235 students (184 graduate students and 51 undergraduate students). The Department of Biostatistics is housed in three different locations: administrative and faculty offices, including a suite of offices for graduate students in McGavran-Greenberg Hall; the Collaborative Studies Coordinating Center ( CSCC) at Carolina Square; and the Carolina Survey Research Laboratory ( CSRL) at Bolin Creek Center.
Position Summary
The BIGS2 (Biostatistics and Imaging Genomics Analysis Lab - Statistics & Signal) Lab https://www.med.unc.edu/bigs2/ is seeking a highly motivated and talented Postdoctoral Researcher specializing in knowledge graph construction and AI development. The successful candidate will collaborate closely with Dr. Hongtu Zhu (Department of Biostatistics) and Dr. Tengfei Li (Department of Radiology) on innovative projects related to Alzheimer's Disease (AD).

The primary responsibility of this role is to synthesize and integrate a vast array of data sources, including imaging, genetic, and clinical data from real-world datasets, alongside extensive literature and other resources. The candidate will be crucial in developing and applying specialized knowledge graphs such as Alzheimer's Disease-related Knowledge Graphs (AD-KG), Omics Knowledge Graphs ( OKG), Neuroimaging Knowledge Graphs ( NKG), and Neuroimaging Omics Knowledge Graphs ( NOKG).

A significant part of this role involves the clinical translation of these knowledge graphs to ensure the research findings can be directly applied to improve patient outcomes. This will include the embedding of these knowledge graphs to facilitate the extraction of actionable insights and enable advanced analyses that can lead directly to enhanced clinical practices and therapies.
The successful candidate will also develop and refine large language models (LLMs) that enhance our understanding of complex datasets, with a focus on implementing KG embedding techniques and performing downstream analysis to measure their impact on predictive accuracy and clinical decision-making.

Furthermore, the role involves designing sophisticated artificial intelligence (AI) agents aimed at advancing analytics in clinical settings and improving decision-making processes in healthcare. This position offers the opportunity to work at the cutting edge of AI, data integration, and knowledge graph technologies, contributing significantly to advancements in medical research and directly influencing the evolution of clinical practices and patient care.

For more information about our lab and ongoing projects, please visit https://bigkp.org/ and https://www.med.unc.edu/bigs2/
Minimum Education and Experience Requirements
Doctorate in Statistics, Biostatistics, Computer Science, Computational Biology, or a related field.
Required Qualifications, Competencies, and Experience
* Proven research experience in data analyses, machine learning, and AI development.
* Experience in one the following three areas: large language models ( LLM), biomedical imaging studies, and genetics data analyses.
* Proficient programming skills in Python, C++, Pytorch, or other relevant languages.

This position involves intensive data analysis and programming, requiring sustained concentration, attention to detail, and the ability to manage multiple tasks efficiently.
Preferred Qualifications, Competencies, and Experience
* Familiarity with knowledge graph construction, natural language processing, or information retrieval.
* Experience in developing and deploying machine learning models, particularly in the context of biomedical or clinical research. Knowledge of advanced AI frameworks such as TensorFlow, PyTorch, or similar.
* Experience in working with human imaging data (e.g., MRI, fMRI) or genetic data.
* Publication record in peer-reviewed journals and conferences.
Special Physical/Mental Requirements
Special Instructions
For information on UNC Postdoctoral Benefits and Services click here Interested candidates should submit the following documents:
* A cover letter detailing your research experience, interests, and suitability for the position.
* A curriculum vitae (CV) including a list of publications.
* Contact information for at least two professional references.
Quick Link https://unc.peopleadmin.com/postings/289885
Posting Contact Information


Department Contact Name and Title Annette Raines, HR Consultant
Department Contact Telephone or Email annette_raines@unc.edu
Postdoctoral Affairs Contact Information
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 (919) 962-9982 or send an email to opahr@unc.edu.

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 of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran.
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