Postdoctoral Fellowships in AI & Medical Imaging

University of Pennsylvania; Meadville (Crawford County); Vor Ort; USD 54.000 - 66.000; Vollzeit

Zusammenfassung

A prestigious research institution is seeking three highly motivated Postdoctoral Fellows for innovative research in machine learning and medical imaging. Candidates will develop advanced methods, apply novel architectures, and utilize computer vision in various applications. The ideal candidate holds a Ph.D. in a related quantitative field and has strong expertise in machine learning and medical image analysis. This role offers a flexible, collaborative environment aimed at pioneering research while contributing to significant projects.

Qualifikationen

• Strong background in machine learning and deep learning.
• Proven ability to conduct independent research.
• Effective collaboration and publication in top-tier venues.

Aufgaben

• Develop advanced statistical and ML methods for neuroimaging.
• Apply novel DL architectures to decode functional connectivity.
• Utilize computer vision for automated health applications.

Kenntnisse

Machine learning

Deep learning

Computer vision

Medical image analysis

Ausbildung

Ph.D. in Computer Science or related field

Ph.D. in Biomedical Engineering

Ph.D. in Applied Mathematics

Ph.D. in Neuroscience

Jobbeschreibung

• 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.

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).

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.