80 distributed-algorithm-"Fraunhofer-Gesellschaft" positions at University of Toronto
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Date Posted: 05/30/2025 Req ID: 37931 Faculty/Division: Faculty of Music Department: Faculty of Music Campus: St. George (Downtown Toronto) Description: JDM3619H Digital Media Distribution A
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edge AI for localized knowledge preservation; AI governance and data sovereignty in digital heritage institutions and collections; study and design of recommendation systems and ranking algorithms used
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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 | 14 days 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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student residences. Responsibilities include greeting residents/guests and visitors, answering questions, transferring phone calls, distributing mail/parcels, monitoring building access, issuing keys and
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 1 day ago
Sessional Lecturer- BIO412H5 F: Climate Change Biology Course description:. Climate change is affecting life on earth at all levels from cells to ecosystems. As a result, shifts in the distribution
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 21 days ago
, valgrind, etc.); solid experience with performance measurements, application profiling, and performance analysis. Must have strong knowledge in Parallel Programming and Distributed Computing. Being familiar
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: Course number and title: MIE1624F/S – Introduction to Data Science and Analytics Course description: The objective of the course is to learn analytical models and overview quantitative algorithms
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technical subjects such as programming, data science, machine learning, and algorithmic fairness is highly desirable. Candidates must have teaching experience in a degree-granting program, including lecture
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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