Postdoctoral Fellowships in AI & Medical Imaging

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.

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.
• 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.

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)

Equal Employment Opportunity Statement

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.