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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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, the project will develop machine learning based solutions for predictive grid analytics (such as grid congestion forecast, asset monitoring, etc.). Based on these results, the project will develop
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, stress markers, EEG, and ECG — will be collected by VR headsets and IoT devices. ML algorithms will analyse this data to identify trends, project risk factors, and propose tailored treatments. By combining
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, such as imbalance and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict
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Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for each project. “Development of natural-ageing-resistant, heat-treatable lean aluminium alloys
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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specifically addresses the identified challenge by leveraging ML to overcome barriers associated with platform heterogeneity, including differences in resolution, scale, and feature representation. By developing
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer