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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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. Simulations are suitable to characterise processes in healthy and diseased individuals including stroke patients. Machine learning methods might be considered to accelerate simulations. The project provides a
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combination of experimental testing and computational modelling (Finite Element Analysis) to create solutions that accelerate the safe deployment of hydrogen aviation technologies. This position is part of
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and accelerate aviation decarbonisation efforts from various roles in industry, academia, government, and policy. The interview process is composed of two interviews. Following a first introductory
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are prepared to lead and accelerate aviation decarbonisation efforts from various roles in industry, academia, government, and policy. The interview process is composed of two interviews. Following a first
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ensures graduates are prepared to lead and accelerate aviation decarbonisation efforts from various roles in industry, academia, government, and policy. The interview process is composed of two interviews
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and accelerate aviation decarbonisation efforts from various roles in industry, academia, government, and policy. The interview process is composed of two interviews. Following a first introductory
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comprehensive understanding of the wider aviation ecosystem. This holistic experience ensures graduates are prepared to lead and accelerate aviation decarbonisation efforts from various roles in industry
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develop a comprehensive understanding of the wider aviation ecosystem. This holistic experience ensures graduates are prepared to lead and accelerate aviation decarbonisation efforts from various roles in