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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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This PhD studentship is an exciting, fully funded opportunity to work as part of an internationally renowned scientific and engineering team to develop a new innovative technology to meet and overcome the serious challenges of increasing dissolved organic carbon (DOC) in the UK’s drinking water...
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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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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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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
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student to work on the SEAI funded InDyCORE (Innovation in Dynamic Cables for Offshore Renewable Energy) project. Power export cables for floating offshore wind turbines, termed ‘Dynamic Cables