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Sessional Instructional Assistant - MAT302H5F - Intro to Algebraic Cryptography (emergency posting)1
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 26 minutes agocryptography, from Euclid to Zero Knowledge Proofs. Topics include: block ciphers and the Advanced Encryption Standard (AES); algebraic and number-theoretic techniques and algorithms in cryptography, including
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developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis of tissue images of cancer using machine learning methods that have been prototyped
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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radio medium, radio communication system examples. Link budget: cable losses, propagation loss, antenna gains. Basic concepts of propagation: path loss, multi-path propagation and fading. Raleigh and
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theoretical foundations, algorithm development, and experimental validation through state-of-the-art robotics and imaging facilities. The Research Coordinator will work closely with students, postdoctoral
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arrangements. Encourage the industrial and academic partners to use UBC’s IntelCut machine tool monitoring system to transfer research algorithms to industry. The engineering activities of IntelCut will be
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Nature Careers | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 3 days ago
learning, statistics, algorithm engineering, bioinformatics, or advanced data visualization. Evidence of effective participation and leadership roles in interdisciplinary research teams, teaching, and
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 11 hours ago
Computer Engineering Fundamentals Algorithms for Computer Engineers Microprocessors Operating Systems Real-Time Systems Computer Security Electrical and Computer Engineering Design Engineering Design II
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machine learning algorithms. It also serves as a foundation for more advanced ML courses. The students will learn about ML problems (supervised, unsupervised, and reinforcement learning), models (linear and
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on Wednesdays and Fridays 11:35-12:55 and labs Mondays 15:35-17:25. This course includes an Introduction to problem-solving methods and algorithm development. Emphasis is on designing, coding, debugging, and