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and AMR markers. By integrating plasmonic signal amplification using gold nanostars with a power-free electrokinetic focusing mechanism, the device will enable early-stage detection without the need
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methods for load identification and modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM
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modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM framework to accommodate new components
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digital signal and image processing, IoT, cyber security, deep learning, and software systems. Applications in healthcare, multimedia, and sustainable urban environments are encouraged. School
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King's College London Department of Engineering | London, England | United Kingdom | about 1 month ago
science interlink prevention and prediction of wildfire risk, by contributing to the development of a fundamental physical model to understand the process of fire spread for wildfires, as part of a European
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to apply: Please choose Electrical and Electronic Engineering Research Program and Control and Power Group, then indicate Professor Balarko Chaudhuri as a potential supervisor when making the application