Postdoctoral Fellowships in AI & Medical Imaging

About the role

We are recruiting three highly motivated Postdoctoral Fellows for NIH-funded positions to drive innovative research at the intersection of machine learning, medical imaging, and clinical data science.

Key Research Areas

• Neuroimaging & Predictive Modeling: Develop advanced statistical and ML methods for large-scale neuroimaging to predict brain age, model disease trajectories, and discover neurological biomarkers.
• Functional Network Modeling & Deep Learning: Apply novel DL architectures and generative models to decode dynamic functional connectivity and brain network organization.
• CT Analysis & Urological Applications: Utilize computer vision and radiomics for automated segmentation, classification, treatment response prediction, and robust multi-site modeling in urological health.

Qualifications

• Education: Ph.D. in Computer Science, Biomedical Engineering, Applied Mathematics, Neuroscience, or a related quantitative field.
• Core Expertise: Strong background in machine learning, deep learning, computer vision, and medical image analysis.
• Agentic AI Focus: A strong interest in, or willingness to learn and develop, Agentic AI applications to enhance medical imaging workflows and research.
• Track Record: Proven ability to conduct independent research, collaborate effectively, and publish in top-tier venues.

Application Instructions

Required documents for upload:

• Curriculum Vitae (CV)
• Research Statement (Highlighting your preferred research areas and how your expertise aligns with or bridges them)
• References: Names and contact information for three professional references (requests will be sent directly through Interfolio)