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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 17 hours ago
% vacation pay Minimum qualifications: Familiarity with scalable technologies such as Apache Spark, Amazon Lambda, Cassandra, MongoDB, Redis, CUDA, Parallel Algorithms, Docker, Kubernetes, Squid. Familiarity
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, this candidate will align computational methods with experimental workflows. The focus will be on developing advanced machine learning algorithms for monitoring various in vitro cell culture models (2D, 3D
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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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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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. We seek applicants who bring an interdisciplinary and critical lens to intervene in global discussions of AI and whose research engages with the design, development, use, and/or evaluation
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, Python, or C/C++, with the ability to develop custom scripts and algorithms for data analysis and modeling. Familiarity with rheological characterization techniques, such as rheometry or viscometry
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developed historically and are ongoing, we strongly welcome and encourage candidates from those communities to apply. Preference will be given to candidates who self-identify as Indigenous. Recognizing
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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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, 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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, lists, maps. Program structure: control flow, functions, classes, objects, methods. Algorithms and problem solving. Searching, sorting, and complexity. Unit testing. Floating-point numbers and numerical