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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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training and guidance to junior undergraduate and graduate students. Education: A PhD in Neuroscience, Computational Neuroscience, Machine Learning in image analysis, or a related field, with significant
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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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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative
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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative
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this will include: Demonstrated expertise in data analysis and simulation Familiarity with C++; and proficiency in the use of ROOT and Geant4, and interest in machine learning techniques Knowledge
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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large
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: - To lead the computational part of a collaborative project on AI-assisted design of OPVs - To become knowledgeable in the field of OPVs and the relevant simulations - To learn relevant machine learning