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analytics (chromatography, Raman spectroscopy, Surface Plasmon Resonance, etc.) Data analysis Machine learning Additional Information Work Location(s) Number of offers available1Company/InstituteUniversité
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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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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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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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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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. 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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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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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
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clinical trials, advanced computational methods, neuroimaging, brain stimulation, body-machine interfacing, gamification of therapy, assistive technology design, development and evaluation, outcome measure
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will be at the rank of Assistant Professor, Teaching Stream, with an anticipated start date of July 1, 2026. Applicants must have a PhD degree in Electrical and Computer Engineering, or a related field