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. Present and defend architecture plans using structured storytelling that blends strategic rationale, stakeholder alignment, and feasibility. Qualifications: A PhD or Masters level education with recent
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Date Posted: 07/29/2025 Req ID: 44537 Faculty/Division: Faculty of Applied Science & Engineering Department: Department of Electrical & Computer Engineering Campus: St. George (Downtown Toronto
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. Present and defend architecture plans using structured storytelling that blends strategic rationale, stakeholder alignment, and feasibility. Qualifications: A PhD or Masters level education with recent
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Studies; Architecture; Museum Studies; Human-Computer Interaction or a related area by the time of appointment, or shortly thereafter, with a demonstrated record of excellence in research and teaching. We
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Studies; Architecture; Museum Studies; Human-Computer Interaction or a related area, with a clearly demonstrated record of excellence in research and teaching. We seek candidates whose research and teaching
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), students will explore the implications of choices in architecture across the range from mainframes and personal computing to mobile devices and sensors, understand the nature of different network and service
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: ITA314H1F – Italian Design: Fashion, Artistry, Genius Section: LEC0101 Course description: “Made in Italy” is a global standard for creativity and excellence in fashion, architecture, and industrial design
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Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps
the everchanging nature of data that is conveyed by the adage “model drifts as data shifts”. Students will use frameworks and techniques for architectural modeling, analysis, and design to understand and apply
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the likelihood of adoption and scale. Qualifications: A PhD or Masters level education with recent experience in clinical and health informatics, preferably in the areas of ICT adoption, implementation, and
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acceptance and adoption in the real-world. Students will use frameworks and techniques for architectural modeling, analysis, and design to understand explainability and fairness in the context of machine