A Deep Learning Engineer designs, deploys, and optimizes deep learning models and algorithms. Responsibilities include training models using frameworks such as TensorFlow, PyTorch, and Keras, as well as evaluating models for accuracy. May work closely with data scientists, software engineers, and other stakeholders to develop solutions that meet business needs.
Perelman School of Medicine Postdoctoral Location University of Pennsylvania – Perelman School of Medicine Open Date Mar 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.
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)
