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qualitative and quantitative methods, processing and analyzing complex datasets, and contributing to the development of computational and machine learning approaches. You will ensure high standards of data
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Supervisor. Assist Professor in preparing, grading, and reviewing HW sets & other assignments, quizzes, exams. Prepare, conduct, and lead tutorials Reading course materials Communication with students
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occasionally be required during early mornings, evenings, and weekends. If selected, specific scheduling arrangements will be discussed between you and the leader. The Role Prepare and present lessons, lectures
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machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics (i.e genomics data including single cell and spatial omics) and drug development applications. Performs analysis
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leadership development opportunity. Our CTF Coach is responsible for supporting students as they work through competitive cybersecurity challenges, support hands-on learning aligned with academic initiatives
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Government of Canada | Government of Canada Ottawa and Gatineau offices, Ontario | Canada | about 6 hours ago
research and design, and develop, assess, and attack cryptographic algorithms and protocols. We’re looking for passionate people from a variety of backgrounds who: • have a blend of math and coding skills
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of recurring processes. Respond to consulting requests requiring expertise in statistical methodologies and procedures. Provide statistical contributions to data mining operations and algorithm development
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analytics and implementation of algorithms in care settings along with clinical, business and ethical challenges will be explored. In addition, an overview of the issues within the health industry
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, developing, and implementing innovative machine learning models and algorithms to drive insights from the hEDS*omics multimodal dataset, encompassing clinical, environmental, and multi-omics data. This role
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measures multi-quantum dot quantum circuits building on a successful process already developed by Salfi’s team in the QMI Nanofab facility [1]. Experimentally investigates and optimizes the performance