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Sessional Lecturer - AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
Study of the United States is seeking to hire one Sessional Lecturer for the following course: Course number and title: AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
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learning with advanced algorithms such as Alphafold3 for molecule processing and foundation models for image processing. Designs and develops machine learning computer models (i.e. algorithms) for medical
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developing image analysis and machine learning algorithms and tools for aerial imaging and analysis. You will also contribute to data collection, data curation, and the development of a data portal for project
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project on convergence analysis of reinforcement learning algorithms for partially observed environments. The position is at the intersection of machine learning, stochastic analysis, and dynamical systems
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Title: Introduction to Computer Science Course Number: COMP 251 - Course Title: Algorithms and Data Structures Course Number: COMP 273 - Course Title: Introduction to Computer Systems Course Number: COMP
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technologies, algorithms, and platforms as required • Produce thorough but concise written documentation of algorithms, workflows, SOPs and other processes and procedures as required • Consult, communicate, and
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, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data
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and synthesize relevant literature in machine learning, representation learning, and manifold learning. Propose and implement extensions to existing dimension reduction algorithms using contrastive
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of new algorithms and technologies. Capturing value from these algorithms and technologies requires an interdisciplinary approach, engaging health and health science professionals in the design and
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degree in Engineering, Computer Science, or a related field. Familiarity with machine learning concepts and algorithms is highly preferred. A basic understanding of audio processing and acoustic analysis