PhD: Deep Learning for Medical Image Analysis

École de technologie supérieure (ETS)
Montreal, Canada
Job Type: 
Full Time
Closing Date: 
Friday, November 30, 2018

Applications are invited for several fully funded PhD positions at the ETS, Montreal, Canada. ETS is the fastest-growing and largest engineering school in Quebec, with an expanding team of highly qualified young researchers in image analysis, one of the priority areas of the school.

In addition to its vibrant, multi-cultural life style, Montreal is currently becoming a hot spot of AI worldwide, attracting major industrial players, which offers excellent placement opportunities to graduate students.

The successful candidates will work under the supervision of Prof. Jose Dolz.

This project will explore semi and weakly supervised learning strategies for understanding and interpreting medical image data, with a main focus on image segmentation. The positions are available after the candidates pass ETS application requirements and they will start at the convenience for the candidates (latest at summer 2019). Financial support is available for 4 years.

Prospective applicants should have:
-Strong academic record with an excellent M.Sc. degree in computer science, applied mathematics, or electrical/biomedical engineering, preferably with expertise in more than one of the following areas: medical image analysis, machine learning, computer vision, pattern recognition, semi/weakly supervised learning and/or optimization;
-A good mathematical background;
-Good programming skills in languages such as C, C++, MATLAB and/or Python.
-At least one publication in a peer-reviewed journal or conference in a related topic.
-They should be able to work both independently and as part of a research team.

Application process: For consideration, please send a CV, names and contact details of two references, transcripts for graduate studies, and a link to a M.Sc. thesis (as well as relevant publications if any) to:

The working language is English (French is not mandatory at all).