University of North Carolina - Chapel Hill
BDC Post-Doc Research Associate
University of North Carolina - Chapel Hill, Elkins Hills, North Carolina, United States
Position Summary
The Renaissance Computing Institute (RENCI) at UNC Chapel Hill is seeking a Postdoctoral Research Associate to contribute to innovative projects within the NIH BioData Catalyst (BDC) ecosystem, a cloud-based platform that provides secure access to biomedical data, analytic tools, and collaborative workspaces. This position offers the opportunity to work on cutting‑edge initiatives aimed at improving how researchers interact with complex data and analysis workflows. Potential project areas include:
Developing semantic search capabilities to help users efficiently locate relevant datasets
Designing natural language interfaces for more intuitive navigation of the BDC environment
Creating BDC‑specific foundation models
Enabling large language models (LLM) and machine learning‑based workflows within the platform
Advancing harmonization techniques to improve data interoperability and usability across the ecosystem
Requirements
Ph.D. in Bioinformatics, Biomedical Informatics, Computer Science, or a related field
Experience deploying and working with LLMs
Experience with agentic workflows and retrieval‑augmented generation (RAG)
Prompt engineering experience
Developing, training, and testing machine learning (ML) models
Software engineering expertise
Preferred Qualifications
Experience with biomedical data, including clinical, EHR, omics, and imaging
Knowledge graphs (KGs), and integrating LLMs with KGs
Multimodal LLMs
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.
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Developing semantic search capabilities to help users efficiently locate relevant datasets
Designing natural language interfaces for more intuitive navigation of the BDC environment
Creating BDC‑specific foundation models
Enabling large language models (LLM) and machine learning‑based workflows within the platform
Advancing harmonization techniques to improve data interoperability and usability across the ecosystem
Requirements
Ph.D. in Bioinformatics, Biomedical Informatics, Computer Science, or a related field
Experience deploying and working with LLMs
Experience with agentic workflows and retrieval‑augmented generation (RAG)
Prompt engineering experience
Developing, training, and testing machine learning (ML) models
Software engineering expertise
Preferred Qualifications
Experience with biomedical data, including clinical, EHR, omics, and imaging
Knowledge graphs (KGs), and integrating LLMs with KGs
Multimodal LLMs
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.
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