617 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "UNIV" "Univ" uni jobs at University of Toronto
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an enthusiastic and innovative professional with extensive experience in law enforcement IT systems, mobile technologies, integrated mobile office environments, multi-agency system integration, data analytics, and
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Date Posted: 02/24/2026 Req ID: 47032 Faculty/Division: Ofc of the Chief Information Officer Department: Enterprise Infrastructure Solutions Campus: St. George (Downtown Toronto) Position Number
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detailed plan for establishing a Public Health research program. The names and contact information of three (3) references Applications will be accepted until April 14, 2026, or until the position is filled
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inquiries in person and on the phone. The incumbent provides support and backup for the other administrative team members as required; compiling materials and other related information for distribution
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. Accuracy and confidentiality in all that you do is a must in this position. Using exceptional client service skills, you will greet telephone callers and the public, providing them with accurate information
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for analytical tasks. This positions is also responsible for assisting the Finance team with projects, as required. Your responsibilities will include: Verifying the accuracy and completeness of information
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of data extraction and appropriateness of supporting documentation. Ensure transactions are processed in accordance with government policies and procedures. To be successful in this position, you will have
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Research Infrastructure field such as data managementlibrary or information studies, computer science, computational sciences, engineering, physics, data analytics, digital humanities, genomics. Five (5
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. Registers patients by collecting all demographic and billing information needed by Health and Wellness (H&W). Answers patient enquiries about available services and about health insurance. Ensures smooth
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Description: STA220H1F L0101 – The Practice of Statistics I (0.5 FCE) An introductory course in statistical concepts and methods, emphasizing exploratory data analysis for univariate and bivariate data