Invigilator Positions


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Teaching assistant and grader positions

Please note the following items apply to all teaching assistant positions:

  • The salary for graduate students serving as teaching assistants is currently $29.33/hour. In exceptional cases where no qualified graduate students have applied to a position, undergraduate students might be hired as undergraduate course assistants, at an hourly rate of $18.00.
  • All information presented on the TA and Grader postings pages (such as the professor and number of hours) is tentative.
  • McGill University is Committed to Equity in Employment.


Fall 2018 TA and Grader Postings

· Teaching Assistant postings can be found at by June 1st, 2018

· Grader postings can be found at by June 1st, 2018.


Summer 2018 TA and Grader Postings


Posting for three (3) TA one (1) grader position in the Department of Electrical and Computer Engineering

  • Course: ECSE 210 Electric Circuits 2
  • Dates: May 01, 2018 to June 18, 2018
  • Hours: 96 hours in total for three (3) TAs (Tutoring/Demoing/Other), 70 hours for one (1) grader (Grading)
  • Duties: The tutorial TA is responsible for conducting weekly tutorials and helps with conducting quizzes. Total hours for the tutorial TA is 30 hours. The lab TAs are responsible for conducting the labs. Total hours for each lab TA is 33 hours.
  • Requirements: TA requires public speaking ability. Must have previously taken this course or equivalent. Preference will be given to doctoral students and to students who have previously been a TA for ECSE-200/210.

For Summer 2018 ONLY, applications should be done via a paper form, to be handed in to the ECE department office, McConnell Engineering Room 633.

Date of posting: March 01, 2018



*** NOTE ***

You no longer have to submit a hard copy of your application for TA or Grader



Other positions

  • For Course Lecturer Positions, please see the separate Course Lecturer page.
  • Please check back frequently for updates.




Probabilistic Vision Group and Medical Imaging Lab McGill University


Announcement of PhD student Position in Machine Learning for
Medical Image Analysis


Position and supervision

We  are seeking applicants for a new PhD student  position in Machine Learning for Medical Image
Analysis, under the supervision of Prof. Tal Arbel and co-supervision of Prof. Doina Precup.
Prof. Arbel [1] is Director of the Medical Imaging Lab and Probabilistic Vision Group – a research group that works on probabilistic methods for computer vision and medical image analysis. This lab is part of the Centre for Intelligent Machines, a world-renowned, interdisciplinary research centre focusing on intelligence systems. Prof.  Precup [2] is Co-Director of the Reasoning and Learning Lab, a group of 50+ researchers interested mainly in machine learning and AI.  McGill  University is located in the beautiful city  of Montreal, a vibrant,  bilingual,  multicultural metropolis in the province of Quebec, Canada.

Research project and team

The research project focuses on the development of new machine learning algorithms for medical imaging, including Bayesian, probabilistic graphical models and deep learning.   Specifically, the candidate will develop theoretical frameworks and software tools to automatically learn Magnetic Resonance Imaging (MRI)  biomarkers for predicting Multiple Sclerosis (MS) disability progression.
The PhD student will join a large collaborative team of researchers worldwide, as part of a recently awarded 4M Collaborative Network Award grant funded by the International Progressive MS Alliance (IPMSA).[3].  The team consists of an interdisciplinary set of researchers including, in addition to com- puter scientists, neurologists and experts in MS, biostatisticians, medical imaging specialists, and mem- bers of the pharmaceutical industry, joining groups from the Montreal Neurological Institute (Canada), Harvard Medical School (USA), University College London Hospital (UK),  University of Genoa (Italy), John Hopkins (USA), and others.  The PhD student will  have  access to an enormous dataset of real, multicenter, multi-scanner, MS patient MRI on which to train and test their frameworks.

Qualifications and informations

The candidate must have completed or being about to complete a M. Sc. or M. Eng. in one of: computer vision, medical image analysis, machine learning. A good track record of publishing in top conferences and journals (e.g. CVPR, MICCAI,  IPMI, PAMI, TMI, MIA, NIPS, ICML) is a strong plus. Candidates must have strong mathematical skills, good programming skills and knowledge and experience in the domain of machine learning and deep learning (e.g.  Python,  Tensorflow/Theano/Pytorch,  C/C++, OpenCV). In addition to conducting independent  research,  responsibilities  will  include collaboration with other members of the IPMSA team and collaborations with other graduate students. Candidates should submit a CV, relevant publications (or projects, blogs, links to repos they deem appropriate), and the names of 2 referees.


All  interested candidates should contact Prof.  Tal Arbel:  arbel [at] or Prof.  Doina Precup: dprecup [at] and cc Prof. Arbel’s research associate Dr. Paul Lemaˆıtre:plemaitr [at] Candidates interested in joining Prof.  Arbel’s lab are advised to submit their application as soon as possible (details for the program can be found in [4]).  McGill  University  is committed to equity in employment and diversity.  It welcomes applications from indigenous  peoples, visible minorities, ethnic minorities, persons with disabilities, women, persons of minority sexual orientations and gender identities, and others who may contribute to further diversification.

Center for Intelligent Machines and Department of 1Electrical and Computer Engineering.

McGill University is committed to equity in employment and diversity. It welcomes applications from indigenous peoples, visible minorities, ethnic minorities, persons with disabilities, women, persons of minority sexual orientations and gender identities and others who may contribute to further diversification. All qualified applicants are encouraged to apply; however, Canadians and permanent residents will be given priority.