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A graduate student (MSc or PhD) is wanted as part of a large, collaborative research project evaluating flood, fire and increasing temperature risks posed to upper Fraser watershed salmon stocks in
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environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning
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staff to produce and revise the academic schedule in accordance with University timelines and policies. Identify and resolve scheduling errors, generate reports, analyze large data sets, and ensure
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high-level content strategies to support the successful achievement of departmental business objectives. This position is responsible for conducting ongoing market research, project evaluation and data
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of building school pride and driving game attendance. We have several large-scale events that we promote and support during the school year along with a steady schedule of games that take place each week during
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in accordance with business requirements Demonstrated experience working with large and complex data sets as well as experience analyzing volumes of data Demonstrated experience in creating data
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and Context: Pediatric neuroimaging research has accelerated the demand for engagement in large multi-centre translational clinical research studies, to enable integrated data exploration and prediction
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within our HubMeta platform. The Postdoctoral Fellow will lead the data cleaning, measurement taxonomy development, and AI-integration phases of the project. Reporting to the Principal Investigator (Dr
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million held at DLSPH, the School contributes to improving population health and health policy and health systems through discoveries and innovation in data science and AI, maternal, child and reproductive
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 25 days ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and