Postdoctoral Fellowships in AI & Medical Imaging

Upenn; Philadelphia (Philadelphia County); On-site; USD 60,000 - 70,000; Full time

Job summary

The University of Pennsylvania, Perelman School of Medicine, invites applications for three postdoctoral fellows to advance NIH-funded research at the intersection of machine learning, medical imaging, and clinical data science. Fellows will explore neuroimaging, predictive modeling, and translational projects across multiple domains.

Candidates should hold a Ph.D. in a quantitative field, bring a strong ML/DL/CV background, and show ability to publish in top venues.

Qualifications

• Ph.D. in a quantitative field relevant to ML/medical imaging.
• Strong background in ML, DL, CV, and medical image analysis.
• Interest in Agentic AI to enhance imaging workflows.
• Proven ability to conduct independent research and publish.

Skills

Machine learning

Deep learning

Computer vision

Medical image analysis

Agentic AI

Education

Ph.D. in Computer Science, Biomedical Engineering, Applied Mathematics, Neuroscience, or related quantitative field

Job description

University of Pennsylvania: Postdoctoral Positions: Perelman School of Medicine Postdoctoral

Location

University of Pennsylvania - Perelman School of Medicine

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.

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), and References: Names and contact information for three professional references (requests will be sent directly through Interfolio)

Application Process

This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.

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.