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National Research Council Canada | National Capital Region Almonte, Ontario | Canada | about 5 hours ago
. To learn more about these options, please contact the NRC Recruitement team using the contact information below. Discover the possible Anything is possible at the NRC, named in 2026 one of Canada’s Top
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National Research Council Canada | National Capital Region Almonte, Ontario | Canada | about 5 hours ago
. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please contact the NRC Recruitment team using the contact information below
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will be excellent teachers and scholars, with the potential to make a significant contribution to scholarship within the area of legal education or the Scholarship of Learning and Teaching. They will
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insights for streaming, broadcast, accessibility and media production. Candidate profile Applicants should have a background in machine learning, audio engineering, speech processing or a related discipline
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researchers. You will (learn to) compete for internal or external research funding. You will assist in teaching lab sessions of relevant courses at bachelor or master level (circa 10% of your time). Profile You
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assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and quantitative security assessment
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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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National Research Council Canada | National Capital Region Almonte, Ontario | Canada | about 5 hours ago
to their communities 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
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for digital patient twins in oncology and cardiovascular medicine. These models should learn patient representations across data types, organs, diseases, and time, capturing disease trajectory, prior history
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. Provides initial project consultations, refers complex research requests to appropriate divisional subject experts, and develops foundational synchronous and asynchronous learning objects. Partners with