Post-Doc Research Associate

UNC-Chapel Hill • Chapel Hill, NC

3d

About The Position

This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models. Responsibilities will include processing and curating large clinical datasets; developing reproducible computational pipelines; conducting internal and external validation studies; evaluating model discrimination, calibration, and robustness; and working with collaborators to interpret study findings. The successful candidate will be expected to lead or make substantial contributions to peer-reviewed publications, conference presentations, and research reports; assist with preparation of grant proposals and regulatory or data-governance materials; document and share research software; and participate actively in interdisciplinary research meetings. Depending on experience and interests, the individual may also mentor graduate and undergraduate researchers and contribute to collaborative projects involving computer science, biomedical engineering, radiology, cardiology, and population health. This position is intended to provide advanced research training and professional development toward an independent career in academic research, industry, or translational biomedical AI.

Requirements

• Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area.
• Strong programming skills in Python and experience with a modern deep-learning framework such as PyTorch or TensorFlow.
• Experience developing, training, and evaluating machine-learning models using complex biomedical, imaging, or other high-dimensional datasets.
• Knowledge of experimental design, statistical analysis, model validation, and reproducible computational research practices.
• Evidence of scholarly productivity through peer-reviewed publications, conference papers, preprints, or comparable research outputs.
• Ability to work both independently and collaboratively within a multidisciplinary research team.
• Strong written and oral communication skills.
• Ability to organize research activities, document methods and results, meet project milestones, and contribute to manuscripts and scientific presentations.

Nice To Haves

• A strong publication record in relevant journals or conferences.
• Prior experience collaborating with collaborators, mentoring junior researchers, or contributing to grant applications.

Responsibilities

• Processing and curating large clinical datasets
• Developing reproducible computational pipelines
• Conducting internal and external validation studies
• Evaluating model discrimination, calibration, and robustness
• Working with collaborators to interpret study findings
• Leading or making substantial contributions to peer-reviewed publications, conference presentations, and research reports
• Assisting with preparation of grant proposals and regulatory or data-governance materials
• Documenting and sharing research software
• Participating actively in interdisciplinary research meetings
• Mentoring graduate and undergraduate researchers (depending on experience and interests)
• Contributing to collaborative projects involving computer science, biomedical engineering, radiology, cardiology, and population health (depending on experience and interests)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree