450 machine-learning-"https:"-"https:"-"https:"-"https:"-"Iscte-IUL" positions at McGill University
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talented Machine Learning Engineer with expertise in healthcare data analysis, medical terminology, and cutting-edge machine learning techniques. The ideal candidate will play a crucial role in designing
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: Desautels Faculty of Management Position Summary: This position includes two parts. Experiential Learning (EL) Student Partners will first learn how to design and develop workshops before working in pairs
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W25 - Biomechanics and Motor Learning Hiring Unit: Department Kinesiology and Physical Education Name & Title of Course Supervisor: TBD Position Summary: This requisition is for one position, at 50
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: Department of Mechanical Engineering Course Title and Course Number: MECH 393 - Machine Element Design Estimated Number of Positions: 2 Total Hours of Work per Term: 90 hours per TA Position Summary: Assisting
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. Job Duties The successful candidate will be involved in the academic activities of the McGill University Department of Neurology and Neurosurgery, Division of Neurosurgery, Brain-Computer Interface. The
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: Optical Fibre Communications; David Plant ECSE 551: Machine Learning for Engineers; Mark Coats ECSE 552: Deep Learning; Course Lecturer ECSE 554: Applied Robotics; Hsiu-Chin Lin ECSE 597: Circuit Simulators
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in maintaining McGill’s international reputation of excellence in research, teaching, and service. We are interested in candidates that apply machine learning and data-driven methods to applications in
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data science. As part of its mission, CDSI offers workshops on topics related to programming languages, data science, machine learning, natural language processing, cluster computing, and advanced
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: Department of Electrical & Computer Engineering Term: Winter 2026 Course subject code: ECSE 552 Course Title: Deep Learning Course Credits: 4 credits Location: ENGMD 279 Schedule: Monday and Wednesday: 8:35 am
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engineering, manufacturing, and artificial intelligence. Responsibilities: Conduct comprehensive literature reviews on machine learning techniques applicable to design-manufacturing integration. Pre-process