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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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, 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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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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promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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; or the training of a machine learning algorithm to read a digitized document written in an under-resourced language. Position description: The University of Toronto Libraries seeks a highly organized, flexible, and
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are designing new artificial intelligence algorithms for a self-driving car. You seek out diverse voices to highlight different experiences that uphold our commitment to equity and inclusion. Outside of long-form
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. Responsibilities As part of the Network Architecture Lab (NAL), the Research Associate will: Design and develop orchestration, analytics, and machine learning algorithms for heterogeneous resource management
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will be expected to independently carry out research projects including formulating problems, developing machine learning algorithms, identifying/compiling/working with carbon mineralization data from