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A Machine Learning Enabled Physical Layer for 6G Radio Systems School of Electrical and Electronic Engineering PhD Research Project Directly Funded UK Students Prof Timothy O'Farrel, Prof Mohammed
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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Early-stage failure prediction in fusion materials using machine learning CDT in Developing National Capabilities for Materials 4.0 PhD Research Project Directly Funded UK Students Prof Christopher
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Machine Learning Methods for Enhancing Autonomy of Unmanned Aerial Vehicles in Wildfire Detection and Localisation School of Electrical and Electronic Engineering PhD Research Project Self Funded
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Machine Learning Methods for Autonomous Robot Navigation, Localisation and Pipe Inspection School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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. This project will develop responsive manufacturing technology that will have sufficient flexibility to overcome such problems by utilizing intelligent machine learning to control the printing process in real
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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
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preferences for them using birds as a model system. Capitalising on recent advances in computational neuroscience and machine learning, specific objectives are to (1) quantify common design features of avian