A postdoctoral position in motion prediction using deep learning for MR-guided interventions, is available at the CHUM Research Center, Montreal, Quebec, Canada, and the MedICAL Lab, Polytechnique Montreal.
The successful candidate should have a PhD degree in Computer or Biomedical Engineering, or Computer Science, preferably with emphasis on motion models for image guided interventions or deep learning. Experience in machine learning and the ability to understand MRI technology are mandatory, while experience in MRI programming and biomechanical simulations or CFD are assets. The candidate should be able to plan and execute practical experiments. Strong knowledge in programming (good experience of C /C++ or python, scripting, and Matlab) are desirable. Teamwork capabilities, good managing and communication skills are required as the candidate will advise PhD students and will present bimonthly report to industrial partners.
The successful candidate will be part of a diverse group including radiologists, radio-oncologists, 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. Samuel Kadoury (samuel.kadoury@polymtl.ca).
A postdoctoral position in image-guided prostate interventions including HDR brachytherapy, is available at the MedICAL lab, Polytechnique Montreal & CHUM research center, Montreal, Quebec, Canada.
The successful candidate should have a PhD degree in Computer or Biomedical Engineering, or Computer Science, preferably with emphasis on image segmentation, image-guidance, tracking systems and image registration. Experience in deformable medical image registration using demons and graph-based approaches is highly desirable. People with computer assisted image guidance background and medical image analysis are particularly encouraged to apply. Strong knowledge in programming (good experience of C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of an optical image guidance system for HDR brachytherapy procedures in prostate cancer, including MRI-ultrasound image fusion and Raman spectroscopy.
The successful candidates will be part of a diverse group including radiologists, radio-oncologists, 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. Samuel Kadoury (samuel.kadoury@polymtl.ca).
A PhD position in deep learning for medical image analysis related to liver cancer is available at the MedICAL lab, Polytechnique Montreal & CHUM research center, Montreal, Quebec, Canada.
The successful candidate should have a Masters degree in Computer or Biomedical Engineering, or Computer Science, preferably with emphasis on deep learning, machine learning and statistical representation. Experience on medical image segmentation using deformable surface, level sets, and graph cut is highly desirable. People with a machine learning background on image features and shape statistics are particularly encouraged to apply. Strong knowledge in programming (good experience of C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of computer aided diagnosis system combining learned image features with patient outcomes for predicting longitudinal progression of liver tumors.
The successful candidates will be part of a diverse group including radiologists, mathematicians, 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. Samuel Kadoury (samuel.kadoury@polymtl.ca).
A PhD position in image-guided catheter tracking in arterial interventions including chemo and radio-embolizations is available at the MedICAL lab, Polytechnique Montreal & CHUM research center, Montreal, Quebec, Canada.
The successful candidate should have a Masters degree in Computer or Biomedical Engineering, or Computer Science, preferably with emphasis on image processing, machine learning, experimental design and clinical testing. Experience on medical image segmentation using graph cuts and level sets, and graph cut is highly desirable. People with experimental science, numerical analysis and image filtering techniques are particularly encouraged to apply. Strong knowledge in programming (good experience of C and C++, scripting, and Matlab) are desirable. The research topic will be the development and validation of an image-based catheter tracking system from fluoroscopic images, fused with pre-operative roadmapping in MRI.
The successful candidates will be part of a diverse group including radiologists, interventional radiologists, 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. Samuel Kadoury (samuel.kadoury@polymtl.ca).
