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Field
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teams to codesign hardware, algorithms, benchmarks and software for QHPC systems, aiming to advance our strategic goals in leveraging quantum computing and high-performance computing (HPC) to develop
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-time reinforcement learning algorithms to personalise training difficulty for the DRUM-AI training app and help shape the future of AI-assisted rehabilitation. The post holder will be based in
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Job Purpose To make a leading contribution to the development of innovative muon tracking algorithms for cutting-edge applied nuclear physics research. The successful candidate will be expected
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meaning from data. Designing machine learning algorithms and undertaking testing for: predictive maintenance. operational performance and cost optimization. failure prevention and timely reparation of Aids
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with implementing these algorithms on fully error-corrected fault-tolerant quantum computers. About You The incumbent is expected to have relevant experience in developing quantum architectures, error
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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success. Basic Qualifications: A PhD in civil, electrical, environmental, or mechanical engineering, or equivalent. A minimum of 1 years of experience in development and testing of algorithmic tools for non
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specialization in Education and Research: The professor will develop research activities in several aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine
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. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial applications. These new initiatives will be integrated into a state-wide
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Professor positions in Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted