Ph.D. in Medical Image Analysis

ETS & McGill University
Montreal, Qc, Canada
Job Type: 
Full Time
Closing Date: 
Wednesday, September 5, 2018

Ph.D. Position in Medical Image Analysis

We are looking for talented, driven and autonomous candidates who are excited about deep-learning, and radiogenomics (radiomics) in healthcare applications. You will work in a multidisciplinary team, helping to review, maintain, design, and develop important algorithms for neuroimaging analysis.

The development and validation of brain tumor segmentation algorithms is a tedious and time-consuming process. Specifically, the segmentation of several tumor levels using deep learning such as convolution neural network is a necessary step. Our goal is to develop MRI segmentation methods to then extract imaging features from segmented tumor regions to predict the survival-time/grade/ treatment…etc. In general, Ph.D. steps will be as follows:

1-Segmentation using CNN models

2-Features extraction 

3-Classification/survival analysis

We're especially interested in candidates who have:

  • An M.E. (or M.S) in biomedical imaging, computer science, statistics, computational neuroscience, or related fields
  • Segmentation, detection, strong machine learning and neuroimaging experience
  • Programming experience in Matlab and Python (ML libraries: Tensorflow, Theano)
  • Great interpersonal and written communication skills


Applicants with prior experience in MRI and medical image analysis will be given highest preference. Candidates should be able to work independently as well as in a team and be highly skilled in written and spoken English, French will assist


The applicant will be co-supervised by Drs (Ahmad Chaddad) and (Bassam Abdulkarim). Work will be done jointly between ETS (A.C.) and McGill University (B.A.),

Interested candidates should apply by sending a brief cover letter describing their previous research experience and current interests, curriculum vitae including publication list and the names of two professional references to The start date for the position is open but should be no later than October 1st, 2018.