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this role, you will work as part of the world-class team of researchers and software developers within the PSS team to develop all or some of firmware, software and algorithms for pulsar and fast transient
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C
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. They will also contribute to outreach activities and be proactive in student recruitment activities. In addition, the successful candidate will contribute to research, enterprise development and knowledge
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs
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work with researchers on the DASS programme to develop and promote freely available software, implementing new statistical methods and algorithms for identifying anomalous structure in stream settings
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position will work with researchers on the DASS programme to develop and promote freely available software, implementing new statistical methods and algorithms for identifying anomalous structure in stream
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Digital twin railway network School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof D Fletcher, Prof R Harrison Application Deadline: Applications accepted all
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computational scientists to develop advanced algorithms and models. Research and validate potential biomarkers associated with breast cancer progression, treatment response, or patient outcomes, using
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at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will involve designing innovative QML approaches and collaborating