Research opportunities

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Intelligent Systems, McGill Edge Intelligence Lab (MEIL), Power Engineering

Immediate Openings


Intelligent Systems

Deep Learning for Medical Image Analysis - January 2023 openings (Deadline for international student applications: July 15, 2022). We are seeking applicants for PhD student positions in deep learning for medical image analysis, under the supervision of Prof. Tal Arbel. Prof. Arbel is a full professor in the Dept. of Electrical & Computer Engineering at McGill University, where she is director of the Probabilistic Vision Group (PVG) at the Centre for Intelligent Machines (CIM). She is a Canada CIFAR AI Chair at MILA, the Quebec AI Institute, and an associate member of MILA and the Goodman Cancer Research Center.

The student will join Prof. Arbel’s vibrant research team whose focus is on the development of probabilistic machine learning and modern deep learning models for medical image analysis, for contexts such as neurological diseases and cancers. Students will help advance one of the open deep learning topics being worked on in the lab, with the overarching objective of building a new framework for image based personalized medicine. Topics include: uncertainty estimation and propagation, knowledge distillation, interpretability/explainability, domain adaptation, cohort bias adaptation and modeling, self-supervision, active learning, multi-modal predictions (e.g. merging clinical and imaging), temporal disease evolution modeling, lesion segmentation, probabilistic lesion detection and counting.

The position will take place in McGill University, located in the beautiful city of Montreal, a bilingual, multicultural metropolis in the province of Quebec, Canada. In addition to joining Prof. Arbel’s team at CIM, the student will join the vibrant machine learning ecosystem at MILA, a community of more than 900 researchers specializing in machine learning and dedicated to scientific excellence and innovation led by Prof. Y. Bengio, a founder of modern deep learning. Through an awarded Collaborative Network Award grant funded by the International Progressive MS Alliance (IPMSA), the student will have access to an enormous dataset of over 10,000 patient real, multicenter, multi-scanner, multiple sclerosis longitudinal patient MRI on which to train and test their models. In addition to computer scientists, the student will collaborate with neurologists and experts in MS at the Montreal Neurological Institute (Canada), biostatisticians, medical imaging specialists, and members of the pharmaceutical industry.

The candidate must have completed a M.Sc. or M.Eng. in one of the following areas: computer vision, medical image analysis, machine learning. A good track record of publishing in top conferences and journals (e.g. CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA, NeurIPS, 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/Pytorch, C/C++, OpenCV). In addition to conducting independent research, the student will regularly collaborate with other graduate students.

All interested candidates should contact Prof. Tal Arbel and CC the MILA Research Scientist at Prof. Arbel’s lab: Brennan Nichyporuk. Candidates should submit a CV, academic transcripts, relevant publications (or projects, blogs, links to github repos they deem appropriate), and the names of 2 referees. Additionally, candidates must apply through the university admission system by following the instructions found here. Please note that the deadline for international applicants is July 15, 2022 for the Winter 2023 term.

PVG is committed to advancing equity, diversity, and inclusion in science. We welcome and encourage applications from underrepresented minorities, recognizing that a diverse community produces the highest quality and most impactful research.


Machine Learning and Bioinformatics - There are openings for PhD and Master students in Prof. Emad's lab in the area of bioinformatics and machine learning. The projects involve developing novel computational methods and algorithms using techniques from machine learning, graph mining, statistical inference and graph theory, to address various problems in cancer genomics and pharmacogenomics. If you are interested in these areas, have a strong programming background, and have knowledge in machine learning, statistics or bioinformatics, contact Professor Amin Emad and include your CV (containing your GPA, publications, relevant courses, etc.).

McGill Edge Intelligence Lab (MEIL)

Deep Learning and Computer Hardware design - There are openings for Postdocs, PhD, and Master students in Edge Intelligence lab in the area of deep learning and computer hardware design. The projects involve developing novel and efficient neural network architectures and algorithms for edge devices (mobile, IoT, wearables). Specific topics of current interest include network compression techniques, hardware-software co-design of neural network systems, and efficient implementation of large-scale deep neural networks. If you are interested in these areas, have a strong programming background, and have knowledge in machine learning, computer hardware design, computer vision and/or natural language processing, contact admin.meil [at] (Professor Warren Gross) and include your CV (containing your GPA, publications, relevant courses, etc.).

Laboratoire d'Intelligence de Pointe (McGill Edge Intelligence Lab-MEIL)

MEIL possède des postes ouverts pour postdocs, doctorat et maitrise dans les domaines de l’apprentissage approfondi et conception de matériel informatique. Les projets impliquent le développement d'architectures de réseaux neuronaux et d'algorithmes nouveaux et efficaces pour les périphériques (mobiles, IoT, portables). Les sujets spécifiques d'intérêt actuel comprennent les techniques de compression des réseaux, la co-conception matériel-logiciel des systèmes de réseaux neuronaux et la mise en œuvre efficace de réseaux neuronaux profonds à grande échelle. Si ces domaines vous intéressent, si vous avez une formation solide en programmation et si vous avez des connaissances en apprentissage automatique, en conception de matériel informatique, et une vision en traitement du langage naturel, soumettez votre lettre d'intention et CV (contenant vos relevé de notes, vos publications, les cours pertinents, etc.) au admin.meil [at] (Professor Warren Gross).

Power Engineering

Post Doctoral, PhD and Master positions are currently available in the area of electric energy systems and electric motor drives, and specifically in microgrid control and operation, the integration of distributed energy resources into distribution systems, intelligent distribution grids and electric vehicle motor drive optimization. Students interested in these areas of study should contact Professor Geza Joos.

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