Postdocs on Medical Segmentation and Registration
Postdoctoral Positions on Learning-based Large-Scale Medical Image Segmentation and Registration
Postdoctoral positions are available in IDEA lab (https://www.med.unc.edu/bric/ideagroup), UNC-Chapel Hill, NC.
Learning-based Image Segmentation: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image feature learning and segmentation. Experience on medical image segmentation using deep learning and shape statistics is highly desirable. People with machine learning background on medical imaging analysis are particularly encouraged to apply. Strong knowledge on programming (good command of LINUX, C and C++, scripting, and Matlab) is desirable. The research topic will be the development and validation of tissue segmentation and ROI labeling methods for brain images, such as infant brain images from our recently awarded Baby Connectome Project (BCP) as well as the elderly brain images from Alzheimer's Disease Neuroimaging Initiative (ADNI).
Large-Scale Image Registration: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on landmark detection, feature learning, and large-scale dataset image registration. Experience on medical image registration is highly desirable. People with experience on pairwise, group-wise and/or longitudinal image registration for large population dataset are particularly encouraged to apply. Knowledge on brain development/aging, machine learning, and deep learning are desirable. The research topic will be the development and validation of learning-based 3D, 4D, and group-wise image registration methods for early brain development or aging studies.
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 (email@example.com).