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. Key Responsibilities Lead AI/ML algorithm development for predicting plant water and nutrient uptake under varying environmental and growth conditions. Analyze multi-source data, including aerial and
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power of data science and algorithmic research with the fields of democratic theory, political science, and public policy. Ideally, the candidate has expertise and interest in innovative research using
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efforts in the Algorithm and Harmonized Data Working Group and other Working Groups/Teams as necessary. Network and Research Administration Facilitates the operationalization of the Canadian Data Platform
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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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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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procedures (e.g., multilevel modeling, longitudinal data analysis, machine learning algorithms), cleaning and structuring large datasets, validating model assumptions, and ensuring reproducibility. Synthesizes
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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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, 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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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum