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: The McGill University Department of Surgery, Division of Vascular Surgery in the Faculty of Medicine and Health Sciences is inviting applications for a full-time Contract Academic Staff position at the rank
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McGill University | Downtown Toronto Commerce Court Victoria Hotel, Ontario | Canada | about 1 month ago
of Minimally Invasive Gynecologic Surgery (MIS), which offers advanced surgical techniques. Minimally invasive techniques using laparoscopy and hysteroscopy provide many benefits to the patient including smaller
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of the University community, and through accommodation policies and procedures . Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence
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The McGill University Department of Pediatric Surgery, Division of Plastic Surgery in the Faculty of Medicine and Health Sciences invites applicants for a full-time position as a member of the Contract
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The McGill University Department of Pediatric Surgery, Harvey E. Beardmore Division of Pediatric Surgery in the Faculty of Medicine and Health Sciences invites applications for a full-time Contract Academic
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, ranging from early devotionals and Bollywood mythologicals to art house and parallel cinema masterpieces to explore key themes in the history and religion of India with a focus on 20th century developments
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, ranging from early devotionals and Bollywood mythologicals to art house and parallel cinema masterpieces to explore key themes in the history and religion of India with a focus on 20th century developments
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literature. Main responsibilities • Design, implement and optimize signal-processing, statistical and machine-learning algorithms for eye-movement (oculomotor) and voice/speech data. • Validate
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practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML
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practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML