Post-Doc Research Associate

UNC-Chapel Hill • Chapel Hill, NC

5d • Onsite

About The Position

A postdoctoral research position is available in the Division of Cardiology at the University of North Carolina at Chapel Hill. The position will support the Division’s research efforts, with primary responsibility in Artificial Intelligence (AI) research focused on cardiology-specific applications. Projects will involve developing, training, and validating AI models using diverse clinical data sources such as ECG waveforms, cardiac imaging, and structured electronic health record (EHR) data. The postdoctoral researcher will work closely with the Director for Cardiovascular Artificial Intelligence Research and contribute to the design of reproducible data pipelines, infrastructure, and translational tools that will support both ongoing and emerging cardiovascular AI efforts at UNC.

Requirements

• Experience supporting or conducting clinical research
• Working familiarity with clinical data types (e.g., ECGs, imaging, structured EHR)
• Ability to critically interpret clinical data, including understanding of clinical documentation, workflows, and disease context
• Understanding of HIPAA, patient privacy, and IRB-regulated research processes
• Strong communication skills, including academic writing or presentation experience

Nice To Haves

• Introductory proficiency in Python, R, or another programming language
• Prior exposure to machine learning or AI techniques in clinical research
• Experience using deep learning frameworks
• Familiarity with cardiovascular data sources (e.g., MUSE ECG, telemetry, cardiac imaging)
• Working knowledge of research infrastructure such as Epic, i2b2, OMOP, or REDCap
• Experience building reproducible data pipelines or deploying research models
• Familiarity with version control (e.g., Git), documentation of code and data workflows, and reproducible research practices
• Experience identifying and troubleshooting data quality issues in real-world clinical datasets
• Demonstrated interest in academic research, digital health, or clinical AI development
• Ability to work both independently and as part of interdisciplinary teams
• Experience identifying and troubleshooting data quality issues in real-world clinical datasets
• Experience with hypothesis testing, statistical analysis, and interpretation

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level