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requirements to verify the accuracy and completeness of information and reconcile both salary and non-salary expenses. Your responsibilities will include: Processing invoices & expense reimbursements, and
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background information, and noting significant activities that require attention/attendance Draft and compile appropriate briefing materials to the VPAP in advance of meetings, including minutes, agendas
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). The candidate will be working on developing state-of-the-art methodology in clinical prediction modeling, including novel uncertainty assessment method (Value of Information analysis), as well as Machine Learning
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McGill University | Edmonton South Westmount Groat Estate East Northwest Industrial, Alberta | Canada | 11 days ago
Abilities Communication skills Bilingualism (English/French), an asset Autonomous and resourcefulness Strong organization skills and attention to detail Knowledge of geographic information systems (GIS
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financial reports Analyzing financial information to identify spending trends, discrepancies, and cost-saving opportunities, including comparing forecasted figures to actuals, conducting salary and benefit
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only. The successful candidate will be hired into the teaching/service pattern (TS). There is an option to change work patterns after tenure. For further information about the position, contact Dr
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information, contact Dr. Charlie Webber, Interim Chair, Department of Education at cfwebber@mtroyal.ca Closing Date: Open until filled; ideal start date of August 15, 2026. Review of applications will begin in
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Loading / Chargement... Help Dashboard Dashboard Dashboard Recruiter Login English English We are sorry this posting does not have information in your chosen language Educational Laboratory
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Loading / Chargement... Help Dashboard Dashboard Dashboard Recruiter Login English English We are sorry this posting does not have information in your chosen language Educational Laboratory
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University of Toronto Faculty of Information Sessional Lecturer Summer Term 2026 – Session Y (May – August) INF2179H – Machine Learning with Applications in Python Course Description: Machine