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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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, regulators, and firms to develop sensible policies and innovative well-being initiatives — which will close significant gaps in industry practices and help to create a more resilient workforce. Applicants
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sectors like aerospace, healthcare, and manufacturing. The convergence of AI with fault-tolerant design principles is transforming traditional maintenance paradigms, leading to more robust and intelligent
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– United Kingdom PhD programme: Harper Adams University PhD programme Fixed term until 30 September 2028 Research project description Agricultural robots and Artificial Intelligence (AI) technologies could soon be
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
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industries and consumers everywhere. This project will help to support Croda’s “Net Zero by 2050” strategy, enabling them to invest in low-carbon, intensified processes that meet their future manufacturing
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. This exciting role offers the opportunity to contribute to cutting-edge research with real-world impact, collaborating closely with industry partners and supporting the transition to more sustainable healthcare
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. Nature-based solutions (NbS) have gained increasing attention in recent years, with the UK at the forefront of deploying NbS to address various environmental challenges. Water Utilities have implemented
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to help Engineer better applications of industrial drop dynamic processes, including inkjet printing and additive manufacturing. Specific research objectives will focus on understanding how microscopic