Job Opportunity

PhD Positions in UNC-Chapel Hill

One PhD position is available, for each of the following research directions, in the IDEA lab of UNC-Chapel Hill, NC (https://www.med.unc.edu/bric/ideagroup).

Brain Image Segmentation and Surface Labeling: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image processing and pattern recognition. Experience on medical image segmentation and analysis is highly desirable. People with machine learning background are particularly encouraged to apply. Knowledge on neuroscience and programming background (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of methods for atlas-based tissue segmentation (of neonatal brain images) and cortical surface labeling of brain images.

Deformable Segmentation: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image feature extraction, 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 statistical deformable segmentation methods for lung, liver, prostate, and brain.

Neuroimage Classification:  The successful candidate should have a strong background on Electronic Engineering, Biomedical Engineering, Statistics, or Computer Science, preferably with emphasis on machine learning, pattern classification, multivariate image analysis, or computer vision. Experience on neuroimage analysis is highly desirable. People with machine learning background are particularly encouraged to apply.

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 (dgshen@med.unc.edu).


Postdoctoral Position on PET/MRI Data Analysis

A postdoctoral position on PET/MRI data analysis 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 sparse learning, super-resolution, and data fusion. Experience on image feature learning, selection, integration and prediction is highly desirable. People with machine learning background on sparse representation and regression 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 image processing methods for integrating PET and MRI for data enhancement and resolution improvement.

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 (dgshen@med.unc.edu).


 

Postdoctoral Position on Infant Brain Segmentation, Registration and Atlas Construction

Several postdoctoral positions are available in IDEA lab (https://www.med.unc.edu/bric/ideagroup), UNC-Chapel Hill, NC.

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 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) is desirable. The research topic will be the development and validation of segmentation methods for infant brain segmentation and surface reconstruction.

Registration: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on feature learning and correspondence detection. Experience on medical image registration is highly desirable. People with experience on pairwise, group-wise and/or 4D registration are particularly encouraged to apply. Knowledge on brain development and also strong background on programming (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of 3D, 4D, and group-wise image registration methods for early brain development study.

Atlas Construction: Candidates with experience on patch-based sparse representation are encouraged to apply. The research topic will be the development of atlas construction methods for infant brain 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 (dgshen@med.unc.edu).



Postdoctoral Position on Machine Learning

A postdoctoral position on machine learning with application to neuroimage-based brain disease diagnosis and prediction is available in UNC-Chapel Hill. The successful candidate should have a strong background on Electronic Engineering, Biomedical Engineering, Statistics, or Computer Science, preferably with emphasis on machine learning, pattern classification, regression methods, or sparse representation. People with strong experience on machine learning are particularly encouraged to apply.

The successful candidate 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. The research topic will be the development and validation of novel machine learning methods for early diagnosis and prediction of brain disorders. Please visit group website (http://bric.unc.edu/ideagroup) for more information.

If interested, please email resume to Dr. Dinggang Shen (dgshen@med.unc.edu).


 

Postdoctoral Positions on Image Segmentation and Registration

Several postdoctoral positions are available in IDEA lab (https://www.med.unc.edu/bric/ideagroup), UNC-Chapel Hill, NC.

Position 1 (Deformable Segmentation): The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image feature extraction, 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 statistical deformable segmentation methods for prostate and brain.

 

Position 2 (Brain Image Registration): The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image analysis, or computer vision. Experience on medical image registration and analysis is highly desirable. People with group-wise registration or 4D registration are particularly encouraged to apply. Knowledge on neuroscience and programming background (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of 3D, 4D, and group-wise image registration methods for brain image analysis.

 

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 (dgshen@med.unc.edu).


Postdoctoral Position on Prostate Segmentation

A postdoctoral position on segmentation of prostate from daily 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 image feature extraction, 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 statistical deformable segmentation methods for segmenting prostate from 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 (dgshen@med.unc.edu).


Postdoctoral Position in 4D Image Registration and Segmentation

A postdoctoral position on 4D image registration and segmentation 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 image analysis, or computer vision. Experience on medical image registration and segmentation is highly desirable. People with machine learning background are particularly encouraged to apply. Knowledge on neuroscience and programming background (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of 4D image registration and segmentation methods for longitudinal image analysis.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 (dgshen@med.unc.edu).


Graduate Research Assistant (GRA)

Graduate research assistant (GRA) positions are available in IDEA lab (https://www.med.unc.edu/bric/ideagroup), UNC-Chapel Hill, NC.

Segmentation: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image feature extraction, 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 deformable segmentation and registration methods for serial CT images of prostate acquired during the radiotherapy of prostate cancer.

Registration: The successful candidate should have a strong background on Electrical or Biomedical Engineering, or Computer Science, preferably with emphasis on image matching. Experience on medical image registration is highly desirable. People with machine learning background are particularly encouraged to apply. Strong knowledge on neuroscience and programming (good command of LINUX, C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of various methods for deformable registration of a set of images, or a set of serial (4D) images from different subjects.

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 (dgshen@med.unc.edu).