533 data-"https:"-"https:"-"https:"-"https:" positions at McGill University in Canada
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: Department of Electrical & Computer Engineering Term: Winter 2026 Course subject code: ECSE 536 Course Title: RF Microelectronics. Course Credits: 3 credits Location: SH680 1255 Schedule: Tuesdays & Thursdays
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the below information as you would like it to appear on the McGill Career Site and delete this line. All other necessary information will appear on the posting automatically and do not need to be included
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in the Client Experience office. Responsibilities will include information distribution, membership sales and general customer service inquiries. Duties Greet and welcome customers Respond to client
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developing electronic career resources and labour market information. This encompasses the organization of the co-curricular experiences inventory and acting as the primary point of contact for students
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experience OTHER QUALIFYING SKILLS AND/OR ABILITIES Desired: Four (4) year degree (Undergraduate) in Management Information Systems or Computer Science or equivalent experience Functional knowledge of IT
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analysing individual interview data from older immigrants Participate in quantitative analysis of survey data Participate in conducting and evaluating pilot intervention in cooperation with community partners
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: Desautels Faculty of Management Course Title and Course Number: Data Analytics in Capital Market ACCT 451/Data Analytics in Accounting ACCT 626 Estimated Number of Positions: 1 Total Hours of Work per Term
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. Maintain CL&E website(s), event calendars and planning tools, gather information to support event preparation, and coordinate venue arrangements, room setups, technological requirements, and day-of logistics
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assistant should be a graduate student or at least have a bachelor’s degree in one of the following academic disciplines or equivalent: sociology, anthropology, data science, political science, psychology
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(GPHL 201) Winter 2026 GPHL 300 Data Literacy (3 credits) Winter 2026 GPHL 300: Introduction to foundational concepts in statistical thinking, data science and epidemiology including how to connect data