Postdoc, Deep Learning in PET/CT Imaging

Tuesday 9th April 2019

Yale University

Yale University Department of Radiology and Biomedical Imaging has multiple positions of postdoctoral fellow for PET/CT imaging research, particularly on the deep learning applications in PET. The candidates will be exposed to unique training and research environments supported by multiple NIH R01 grants and strong Academic-Industrial Partnerships. The fellows will have access to power computational resources and large amount of training dataset. Research projects will focus on incorporating deep learning methods into dose-reduction techniques and motion correction methods for PET/CT. 

Applicants should have a Ph.D. in electrical engineering, biomedical engineering, computer sciences, medical physics, or a related field. Strong analytical, programming, and experimental skills are essential. Experience in deep learning, image analysis, algorithm development, or image reconstruction is highly desirable. 

Interested individuals should send a C.V., letter of interest, and contacts of three references by email to Dr. Chi Liu (chi.liu@yale.edu), Associate Professor of Radiology and Biomedical Imaging, or Dr. James Duncan (james.duncan@yale.edu), Professor of Radiology and Biomedical Imaging, or Dr. Xenophon Papademetris (xenophon.papademetris@yale.edu) Professor of Radiology and Biomedical Imaging.

Location New Haven, CT, USA
Title Postdoc, Deep Learning in PET/CT Imaging