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partners both in the UK and internationally, joining a supportive group of researchers within the wider research group, the School, and across the University of Southampton. To succeed, you will need a PhD
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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the processes impacting outdoor and indoor air quality. You will work with a team of researchers using CFD and Machine Learning approaches to apply these results towards modelling and understanding the physics
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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment