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Early integration of sensors for efficient SHM of aerostructure during their service. Using a mix of reactive machines and limited memory this project develops new fuzzy logic based artificial intelligence (AI) algorithms for SHM system integration. The research will focus on early...
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-vibration problems came to light, indicating that modern, light-weight, low-frequency and lightly-damped structures have to be designed with new standards, grounded on a theoretical framework for human
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for Embedded Machine Learning Applications," funded by the NorthEast Launchpad Competition. We are seeking a candidate with a strong background in hardware design and the implementation of machine learning
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remained unclear for decades, and thus design principles for discovering new thermal battery materials have been lacking. In this industrially sponsored PhD studentship, we have partnered with AWE to fund a
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information yielded by this study will allow us to develop design principles for new Na-ion battery cathodes with improved electrochemical performance. Promising candidates will be experimentally tested through
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, as well as in designing coordination strategies. Our recent work on ML-based co-optimization demonstrates some of our key research directions relevant for this position. The role holder will work
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Funding providers: EPSRC and STRIP5 Prosperity Partnership Subject areas: Photovoltaics, Perovskites, Module design, Engineering Project start date: 1 October 2024 (Enrolment open from mid-September
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the processing that is conducted on the chip. This requires an efficient and bespoke processor design that maximises the processing speed on the chip for the algorithms that are required for facial expression
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Project Overview This project is at the intersection of machine learning, differential equations, and numerical weather prediction (NWP). This collaboration with the Met Office integrates advanced mathematical models with state-of-the-art machine learning techniques to develop forecasting models...
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design, Engineering Project start date: 1 October 2024 (Enrolment open from mid-September) Supervisors: Professor Trystan Watson ([email protected] ) Dr Eifion Jewell Dr David Beynon Aligned