Postdoctoral Fellowships in AI & Medical Imaging
Listed on 2026-09-02
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer, AI Engineer (Applied/Software) -
Research/Development
Data Scientist
University of Pennsylvania:
Postdoctoral Positions:
Perelman School of Medicine Postdoctoral
University of Pennsylvania - Perelman School of Medicine
Open DateMar 26, 2026
Description- Faculty Mentor:
Yong Fan, PhD (Yong Fan, Ph.D. – AIBIL) - Department:
Radiology - Funding Source: NIH
- Number of positions: 3
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. We offer a flexible, highly collaborative environment where fellows can dive deep into a specific domain or pioneer research across multiple fields.
Key Research Areas (Candidates may focus on one or bridge multiple domains)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.
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.
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