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healthcare environment Strong financial acumen, including financial analysis, budgeting, and forecasting experience Experience developing high functioning teams, including a proven track record of success in
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independent research at the highest international level and to maintain an outstanding, competitive, and externally funded research program. Candidates must provide evidence of research excellence demonstrated
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candidate will be expected to pursue innovative and independent research, and to establish an original, competitive, independent, and externally funded research program as well as expected to contribute
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of Toronto. Spaces & Experiences develops and supports high-quality innovation space, housing for faculty and students, food service locations (retail and residential) and ancillary retail space to serve
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the incumbent to the tasks indicated. Flexibility of the employee to perform a wide variety of functions is necessary in successfully fulfilling the requirements of this position. The degree to which each
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computer-aided design and manufacturing (CADCAM), utilizing a variety of materials (e.g. wood, fabric, metal, plastics & thermoplastics)and components (e.g. fasteners, microcontrollers, arduino, tubes, gears
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Identifying and introducing variations to established administration processes Performing financial responsibilities including making minor purchases, collaborating on cost estimates and processing accounts
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
independent research at the highest international level and to establish an outstanding, competitive, and externally funded research program. Candidates must provide evidence of research excellence which can be
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
innovative and independent research, and to maintain an outstanding, competitive, and externally funded research program. The successful candidate’s research will focus on one or more of the LEMM areas
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examines state of the art techniques and technologies related to explainability and fairness in machine learning applications. These human-centric aspects play a significant role in the design and operation