Postdoctoral Associate

School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,600 faculty physicians and researchers, nearly 2,000 students, and more than 6,200 staff, the Duke University School of Medicine along with the Duke University School of Nursing, and Duke University Health System comprise Duke Health, a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations.

Be You.

The Quantitative Imaging and Analysis Laboratory in the Department of Radiology at Duke University is seeking a Postdoctoral Associate to join our team. In this role, you will work on the development and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning.

The position will involve work across several NIH-funded research projects in preclinical and translational imaging. Current projects include spectral photon-counting CT of cerebral vasculature and intracranial aneurysms, photon-counting CT and computational imaging of head and neck cancer, and multiorgan CT studies of aging and cardiovascular disease.

The Postdoctoral Associate will have the opportunity to work on topics including:

• Photon-counting and spectral CT imaging
• CT reconstruction and image-processing methods
• Material decomposition and quantitative spectral imaging
• Image segmentation, registration, and quantitative morphometry
• Machine learning and deep learning for CT image analysis and reconstruction
• Computational and digital-twin models for preclinical imaging
• Analysis of longitudinal and dynamic imaging data
• Development and validation of imaging biomarkers

The work will combine method development with analysis of experimental imaging data. There will also be opportunities to participate directly in preclinical imaging studies and in the development of new imaging protocols.

Minimum Requirements:

• Ph.D. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) in biomedical engineering, electrical or computer engineering, medical physics, computer science, applied physics, or a closely related field. Candidates with non-US degrees may be required to provide proof of degree equivalency.