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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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with multivariate statistics, machine learning, and/or remote sensing would be an asset. Experience and education: Ph.D. degree in geography, agriculture/agronomy, environmental science, or a related
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of Dr Benoit Gosselin (Université Laval), Guillaume Lajoie (UdeM) and Marco Bonizzato (Polytechnique). It integrates the use of machine-learning approaches to optimize neurostimulation, automation
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning