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application of these techniques to the domain of information science. Topics will include software principles and practices, programming concepts and techniques, data structures, and algorithms. This course is
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the knowledge and tools required to balance time and resources between teaching, research, and administration. Estimated Enrolment: 40 PhD candidates and postdoctoral fellows Number of Positions: 1 Posting end
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there is a change to the date/time) Location: Chancellor Day Hall Course Description: Technology law of how to regulate AI algorithms. How technological innovation produces social change: human
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Megan Thomas Doctor of Philosophy in Pharmaceutical Sciences (PhD) Addressing equity considerations in research and care of patients with inflammatory arthritis View All Stories Further Information
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Enrollment Limit: 25-30 Location: Saskatoon Qualifications: Minimum of a Master’s degree but PhD preferred in public administration, public policy, political science, or a related discipline. Experience in a
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Number: COMP 251 - Course Title: Algorithms and Data Structures Hours of work (per term): 90 Required duties: • - effectively and timely communicate with the instructor and the students; • - maintain
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Number: COMP 360 - Course Title: Algorithm Design. Hours of work (per term): 90 Required duties: • - effectively and timely communicate with the instructor and the students; • - maintain and observe
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work independently on complex projects. Experience and Education Master’s degree in Software and Computer Engineering (French engineering schools are preferred). Experience in optimizing ML algorithms
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, strings, pointer-based data structures and searching and sorting algorithms. The laboratories reinforce the lecture topics and develops essential programming skills. Estimated course enrolment: ~150
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a training dataset for developing machine learning algorithms for increasing the consistency of quality control in two cohort studies: healthy controls and epilepsy patients. Key Responsibilities