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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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Applications are invited for a PhD studentship in the Centre for Human-Computer Interaction Design, based in the Department of Computer Science. The successful candidate will undertake PhD research
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flooding events and recreation in freshwater. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security
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health genomics, combining academic research with front-line public health intervention experience. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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and brain tissue mechanics to improve stroke treatment. Stroke is a leading cause of death and disability worldwide, making advancements in its diagnosis and treatment highly relevant. Computational
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programme +2 - covering 2 years of study for current postgraduate researchers 1+3 - covering Master's and Doctoral study Please see Additional Information for 1+3 and +2 application processes. Tenable period
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for...
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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in