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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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operations. The postholder will be supported to develop their skills in a variety of areas, including Power Automate, Power Apps, Power BI, and software testing. The role will also include opportunities
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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project will develop novel methods for modelling and controlling large space structures (LSSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. Working with leading
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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provide the essential human-state awareness required for trustworthy autonomy. The second area centres on trust-adaptive autonomous behaviour design. Here, the candidate will develop embodied vehicles
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling