145 structural-engineering-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Toronto in Canada
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the principles and methods of information retrieval through academic and professional database searching. Characteristics of database organization, structure, and content, question analysis, search development and
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: The Acceleration Consortium (AC) is leading a revolutionary shift in scientific discovery that is accelerating technology development and commercialization. The Consortium, a coalition of entrepreneurs, technology
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the world. The Schwartz Reisman Institute for Technology and Society is a highly specialized research, policy and solutions initiative at the University of Toronto that draws on world-class research
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redevelopment projects for academic and research purposes, space and technology Experience leading, mentoring and supporting the professional development of senior staff Proven experience collaborating across
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 3 hours ago
the University, knowledge of university policies and procedures, and an understanding of the University’s organizational structure, including its governance. Experience advancing equity projects within a post
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with proven ability and interest in supervising employees and performing maintenance procedures. The ideal candidate will bring both a Fireman's Boiler Operator Certificate and a Refrigeration Engineer
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place Indigenous knowledge systems, cultures and languages within structures, policies and curricula. The Ministry of Education is advancing reconciliation with early years, Prekindergarten to Grade 12
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and analyze data Essential Qualifications: Bachelor's Degree, STEM degree or technology background; or acceptable combination of equivalent education and experience. Master of Business Administration or
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Position: Sessional Lecturer Department: Engineering Communication Program Course number and title: ESC102H1 S – Praxis II Course description: Praxis II follows from Praxis I and challenges students
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biosynthetic gene clusters and other molecular features relevant to natural product drug discovery Validating machine-learning and deep-learning models to predict the chemical structures and bioactivity