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or information technology. The course will cover material that is relevant to health informatics and focus on the understanding of hardware and software systems. We will focus on the proper design and
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Course Description: In Complexity of Clinical Care, the implications and practical application of the outputs of AI and Machine learning are discussed in class, and in select assigned readings. This class
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 2 months ago
team in the AI in Medicine Lab (www.aimlab.ca ). This position is based in the School of Biomedical Engineering. The successful candidate will work in the AI in Medicine Lab, applying machine learning
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position in experimental chemistry, with a preference for candidates able to teach in the areas of physical chemistry, inorganic chemistry or organic chemistry. The research area is broadly defined and
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expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be a part of the Walk Tall research team based at BC Children’s Hospital. The Postdoctoral Fellow will
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standards across the various academic divisions, as well as supporting postdoctoral fellows. SGS defines and administers University-wide regulations for graduate education. We share responsibility
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
justification process . Applicants must have earned a PhD degree in biology, biomedical sciences, computational biology, AI/machine learning, bioinformatics, or a related area to the subject matter of this search
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to take a lead with industry stakeholders as well as teach in the Soil Science, Environmental Science and Renewable Resource Management degree programs and other associated certificates and degrees within
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Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a closely related technical field. Demonstrated knowledge of or interest in Indigenous Knowledge Systems and interest in applying IKS
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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image