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down the AMOC, which is highlighted as a global tipping point of major concern by the Intergovernmental Panel on Climate Change (IPCC). This project seeks to understand the operation of this sub-polar
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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, embedded systems, advanced implant probe design and signal processing. There are opportunities for students from a variety of backgrounds to work on the following possible projects: Bionic Vision
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/learning based techniques in the areas of robotics, or autonomous systems, • interested in autonomous systems and signal processing, • Keen to work with equipment and embedded
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-culture studies to evaluate mechanotransductive signalling. The resulting data will inform mathematical models linking material mechanics to biological responses, enabling the sustainable design of next
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the University admissions procedure. You will be required to submit supporting documents including: transcripts, degree certificates, a research proposal, your CV and references. When making an application, you
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explore multimodal learning and unlearning techniques using vision, language, and audio signals to build intelligent systems capable of interpreting and responding to human actions and emotions. This work
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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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and reliability. You will integrate, adapt and develop methods (using packages such as BioSPPy) for the processing and analysis of physiological signals measured for determining deception. The project
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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