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research projects. Qualifications: PhD in Computer Science, Information Science, or Engineering. A minimum of five peer-reviewed publications in data mining, machine learning, AI, or cybersecurity. At least
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, topographic data, land-cover data, and other environmental predictors. Designs and evaluates statistical and machine-learning approaches for modelling plant species distributions and assessing environmental
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expertise in fire behaviour and climate modelling, remote sensing, and machine learning to a multidisciplinary research program that spans prescribed fire operations, fire behaviour modelling, IoT sensor
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of policies and procedures and the day-to-day administration of over 60 MSc and PhD students. They coordinate the extended learning programs within the IOF, including Future Global Leaders, Vancouver Summer
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or machine learning Experience with Swift development and/or strong willingness to work within the Apple development ecosystem Experience in edge AI, model optimization, or deployment of AI models
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research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the
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and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please
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multivariate, statistical-genetic or machine-learning approaches. · Research involving developmental, ageing or neuropsychiatric cohorts, including longitudinal or large-scale population datasets. · High
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of inverse photonic design, machine-learning (adjoint or topology optimization), or other advancing design methodologies. Ability to design and model active photonic devices (MEMS, electro-optic or thermo
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/or adapt machine learning and artificial intelligence approaches for the analysis of spatial and multispectral imaging datasets, including transcriptomic, proteomic, and lipidomic data derived from