A postdoctoral position on segmentation of pelvic structures (including prostate) from planning and daily treatment CT images is available in IDEA lab (https://www.med.unc.edu/bric/ideagroup), UNC-Chapel Hill, NC.

The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on deep learning, shape representation, and shape statistics. Experience on medical image segmentation using deformable surface, level sets, and graph cut is highly desirable. People with machine learning background on image features and shape statistics are particularly encouraged to apply. Strong knowledge on programming (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of learning-based segmentation methods for extracting pelvic structures from planning and daily treatment CT images.

The successful candidates will be part of a diverse group including radiologists, psychologists, physicists, biostatistician, and computer scientists, and will build upon the group's previous work on medical image analysis. If interested, please email resume to Dr. Dinggang Shen ([log in to unmask]).