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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 19 days ago
of the law to practical problems and case settings. Topics include computation of corporate taxes, integration, corporate reorganizations, surplus distributions, partnerships and trusts. Job Details Job Title
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prepare, approve and distribute a variety of post-court documents, ensuring legislative compliance; and Providing assistance to clients and information in response to general inquiries. Our candidate
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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maintaining research databases and records including accurate data entry, coding of quantitative research data, and generating reports Experience taking and distributing meeting minutes Experience handling
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at eitan.amir@uhn.ca The Department of Medicine at the University of Toronto is one of the oldest and largest in North America with over 700 full-time faculty members distributed across six fully-affiliated
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, supporting events and programming, and collaborating to identify variations to administrative processes. Your responsibilities will include: Applying established standards to control the distribution of access
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are handled in compliance with defined protocols. Creates, runs and exports analytical reports to support member libraries. Prepares and distributes LSP-related documentation; contributes to the development and
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resolving payroll discrepancies Reconciling payroll distribution Generating standard financial reports Essential Qualifications: Advanced College Diploma (3 years) or acceptable combination of equivalent
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, install, and configure servers. Setup, manage, and maintain the equipment in high computer data rooms. Experience with enterprise electrical systems and power distribution, with an understanding
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred