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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 19 days ago
(Introduction to Software Engineering), CPSC_V 314 (Computer Graphics), CPSC_V 317 (Introduction to Computer Networking), CPSC_V 319 (Software Engineering Project), CPSC_V 320 (Intermediate Algorithm Design and
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of Commercial Contracts law • Knowledge of Contracts Negotiations • Knowledge of Technology Products Analysis (algorithms, analog/digital devices • Knowledge of Venture Market Analysis /Venture Business Strategy
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), debuggers, code verifiers and unit test frameworks and gain experience in graphical user interface design and algorithm development. Posting end date: July 11, 2025 Number of positions (est): One (1) position
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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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including access point provisioning, asset management, access point / antenna installation, site-surveys and end-user equipment testing. Provides equipment racking functions and fibre backbone patching in
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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