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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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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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Engineering Research Associate: Advanced Renewables At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning
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. This posting is to fill an existing vacancy within the University. Qualifications Candidates must have a Bachelor’s degree and a PhD in Electrical and Computer Engineering or equivalent degrees completed
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on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day. The Department of Electrical and Computer Engineering has
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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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Successful applicants will have: PhD and postdoctoral fellow training with expertise in cancer biology, proteomics and/or computational biology / machine learning A proven track record with first author
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 1 month ago
PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or PhD or equivalent degree in population/public health and other related medical fields with AI and ML
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 7 days ago
. Demonstrated expertise in data science, statistics, or machine learning, with research experience in health research, statistical physics, or geroscience. Strong analytical, computational, and quantitative
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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