483 education-technology-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in canada
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data Prior experience teaching this course (or a similar course) at the university level Ability and experience teaching large classes Preferred qualifications: Industry experience in predictive modeling
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 1 month ago
Hygiene. The normal workload distribution for these positions is approximately 80% teaching and course administration and 20% service. The primary role of the Program Co-Leads is to provide academic and
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: LIN211H1S – American Sign Language 1 Course description: This course is an introductory language course for students with little or no prior knowledge of American Sign Language (ASL). It provides an immersive
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designing and creating optimal processes and procedures to systematize the data reporting process. The incumbent will use advanced data modeling, predictive modeling, and analytical techniques to develop
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work with us? We offer access to advanced technologies and equipment; a progressive supportive work environment; opportunities for job advancement and continuing education; team approach to patient care
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Instructional Assistant Course number and title: HMB306H1F – Ethical Considerations in Emerging Technology Course Description: Advancing technology increases our ability to intervene in the course of natural
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during the final application process. Please see the CRC website for additional information about self-identification . Building on a foundation of excellence in liberal education, the University
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Sessional Lecturer - CTL3796H - LLE Practicum for MEd Field in Language Teaching Course number and title: CTL3796H - LLE Practicum for MEd Field in Language Teaching Course description: : LLE M.Ed
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Sessional Lecturer - CTL3796H - LLE Practicum for MEd Field in Language Teaching Course number and title: CTL3796H - LLE Practicum for MEd Field in Language Teaching Course description: : LLE M.Ed
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The University of Toronto requires that candidates must have a Ph.D in Electrical and Computer Engineering, Computer Science, or a related field, with a demonstrated record of excellence in research and teaching