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health management (IVHM) system that leads to enhance safety, reliability, maintainability and readiness. Generally, prognostics models can be broadly categorised into experience-based models, data-driven
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to enhance real-time data collection and improve monitoring practices, and the social factors that influence their uptake. This studentship offers a unique opportunity to engage in groundbreaking research with
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international fees. Costs that must be found from other sources or met by the individual student include: visa fees, healthcare surcharge, relocation costs and guarantor services. For up to date information
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usability and accuracy, as well as conducting field tests to validate their effectiveness. Additionally, the research will explore the economic viability of these sensors to enhance real-time data collection
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influence perceptions. It will subsequently explore and evaluate the types of information and knowledge required to improve the understanding and appreciation of urban blue spaces, before investigating
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responses and mitigation scenarios across realistic European agricultural landscapes (illustrative example shown in Figure 1). There is also an opportunity to collect original movement and behavioural data
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capable of dynamically adjusting their collaboration strategy—such as autonomy level, motion behaviours, and information transparency—based on real-time human trust. By aligning vehicle behaviour with
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extracting useful knowledge from remote sensing data. About the Role To carry out research involving the integration of drone-based imaging, multispectral data analysis, phenotyping techniques, and the
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of technology to underpin and evidence the apprentices learning and support the journey towards successful apprenticeship completion. About You You will have sound knowledge of data protection regulations and be
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for the collection of data to develop and validate prognostic models for filter degradation. Integrated Drive Generator (IDG) Rig: Simulates the operation of an aircraft's IDG, used to investigate fault detection