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McGill University, Department of Mathematics and Statistics Position ID: McGill-STATS [#26987] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Montreal, Quebec H3A 0B9
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area: Reinforcement learning; probabilistic approaches in machine learning; mathematical foundations of machine learning. Previous experience as an instructor at the university-level is required. Related
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: Department of Mathematics and Statistics Course Title and Course Number: Topics in Probability and Statistics MATH 587 & Advanced Topics in Statistics I MATH 782 Estimated Number of Positions: 1 Total Hours
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science, mathematics, or a related field in the Quebec educational system 3.Knowledge of the Quebec Education Program (QEP) 4.Familiarity with the professional competencies specified by the Ministère de
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: Mechanical Engineering Course Title and Course Number: Applied Mathematics - MECH 605 Estimated Number of Positions: 1 Total Hours of Work per Term: 50 Position Summary: Marking of assignments and midterm
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, Mathematics). Includes historical perspectives, and emphasis on ways of thinking that cut across the arts and STEM, such as design-based thinking. Term: Winter 2026 Course Credits: 3 Location: EDUC 360 Schedule
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, mathematics, or a related field in the Quebec educational system 3. Knowledge of the Quebec Education Program (QEP) 4.Familiarity with the 13 professional competencies specified by the Ministère de l’Éducation
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: Department of Mathematics and Statistics Exam Period : • MATH 314 - October 20th 2025 (6:00pm-9:00pm plus setup and takedown) Position Summary : • Responsible for setting up the examination room according
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: Department of Mathematics and Statistics Exam Period : • MATH 271 - October 20th 2025 (6:00pm-9:00pm plus setup and takedown) Position Summary : • Responsible for setting up the examination room according
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thinking and practice 2.Experience as a master teacher/instructor science, mathematics, or a related field in the Quebec educational system 3.Knowledge of the Quebec Education Program (QEP) 4.Familiarity