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criteria Candidates will be assessed on the basis of the following criteria: Technical competencies Basic knowledge of machine learning techniques as applied to high-throughput materials research and
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applications for machine learning. Technology Assessment: Evaluate emerging technologies, instrumentation devices and other tools related to power electronics for electric vehicles applications. Collaboration
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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 contact the NRC
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of the following criteria: Technical competencies Knowledge of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates
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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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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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of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates to experimental data and ability to automate data storage
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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