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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
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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overlook the impact of liquid metal convection within the molten pool. Although using an artificial compensation through calibration with experiments can improve the temperature prediction, the predictive
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
techniques (e.g., ultrasonic C-scan, X-ray CT, thermography) rely heavily on expert interpretation, are time-consuming, and often fail to detect subsurface or latent damage accurately. Advances in artificial
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: The project will adopt a mixed-methods approach: - Data collection: Deploy camera traps and artificial flower attractants across urban and agricultural sites to capture pollinator activity. - Model development
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. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has
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-Royce, Thales, and UKRI—offering global relevance in low-power AI hardware, embedded intelligence, and adaptive electronics. The rapid advancement of Artificial Intelligence (AI) has necessitated