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Announcement of Postdoctoral Fellow Position in Medical Image Analysis

last modified 2017-05-04 16:19

Probabilistic Vision Group and Medical Imaging Lab, Center for Intelligent Machines & Department of Electrical and Computer Engineering, AND Reasoning and Learning Lab, School of Computer Science McGill University

The Department of Electrical and Computer Engineering and the School of Computer Science, McGill University, are inviting applications for a Postdoctoral Fellow position in the field of Medical Image Analysis. The successful candidate will work under the joint supervision of Profs. Tal Arbel and Doina Precup. Prof. Arbel is Director of the Medical Imaging Lab and Probabilistic Vision Group – a vibrant research group that works on probabilistic methods in the context of both the fields of 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 is co-director of the Reasoning and Learning Lab. McGill University is located in the beautiful city of Montreal, an exciting, bilingual, multicultural metropolis in the province of Quebec, Canada.

The research project focuses on the development of new machine learning and computer vision frameworks to automatically learn Magnetic Resonance Imaging (MRI) biomarkers for predicting Multiple Sclerosis (MS) disability progression in patients with progressive MS for use in clinical trials. The postdoctoral fellow will join a large collaborative team of prominent researchers worldwide, as part of a recently awarded €4 million Collaborative Network Award grant funded by the International Progressive MS Alliance (IPMSA) (Website). The team consists of an interdisciplinary set of researchers including neurologists and experts in MS, biostatisticians, medical imaging specialists, and members 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), The University of Texas Health Science Center (USA) and others. The postdoctoral fellow will have access to an enormous dataset of real, multicenter, multi-scanner, MS patient MRI acquired in hospitals and during clinical trials on which to train and test their frameworks. In addition, a dedicated NViDIA DGX-1 Deep Learning machine will be purchased for the project.

The candidate must be have a PhD in the domains of computer vision/medical image analysis/machine learning with preference given to candidates that have published in top conferences and journals (e.g. CVPR, MICCAI, IPMI, PAMI, TMI, MIA, NIPS, ICML). Candidates must have strong mathematical skills, good programming skills and knowledge and experience in the domain of machine learning (e.g. C/C++, OpenCV, Theano). Accepted candidates will be expected to write conference and journal papers, and strong English writing skills will be required. In addition to conducting independent research, responsibilities will include collaboration with other members of the IPMSA team and supervision of graduate students. Preference will be given to applicants from well-established groups. Only candidates with strong reference letters will be considered. Postdoctoral fellowships can commence right away. All interested candidates should contact:
Prof. Tal Arbel: arbelATcimDOTmcgillDOTca or Prof. Doina Precup: dprecupATcsDOTmcgillDOTca