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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal
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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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algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions. The student will undertake two industry placements at Spirent, use high-tech simulation
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refine simulation tools and machine learning solutions to advance stroke treatment. This involves improving existing computational models that simulate cerebral blood flow, oxygen distribution, and brain
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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