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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
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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
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a training dataset for developing machine learning algorithms for increasing the consistency of quality control in two cohort studies: healthy controls and epilepsy patients. Key Responsibilities
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. The ultimate objective is to develop a next generation of AI approaches that are more sustainable and accessible. Relevant domains include mathematical and computational optimization, learning algorithms
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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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unit test frameworks and gain experience in graphical user interface design and algorithm development. Estimated course enrolment: ~360 Estimated TA support: TBD Class schedule: Timetable Builder
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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
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of new algorithms and technologies. Capturing value from these algorithms and technologies requires an interdisciplinary approach, engaging health and health science professionals in the design and
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data algorithms. Experience in organizing, coordinating, and managing research projects as evidenced by a minimum of five grant-based research programs. A clear understanding of the academic research