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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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implementing quality assurance and quality control (QA/QC) test Designing testbenches, and contributing to firmware programming for state-of-the-art FPGA architectures, primarily Intel FPGAs. Collaborating
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architectures, primarily Intel FPGAs. The successful candidate will collaborate closely with researchers at McGill and partners worldwide, leveraging industry-standard tools and technologies to ensure
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. Qualifications: A doctoral degree in epidemiology Knowledge of advanced epidemiologic methods Strong data manipulation and analytic skills using statistical programming software, e.g., SAS Demonstrated ability
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 19 days ago
part of their research program in another field. 2. An interest in open source instrumentation development (software and/or hardware). 3. Proficiency in programming (C, C++, Java or python). 4
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methods is an asset Knowledge of Bayesian statistics is an asset Excellent written and oral communication skills Strong analytical, problem-solving, and programming skills (in statistical software such as R