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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
artificial intelligence, machine learning, data analysis, or digital systems would be advantageous but is not essential. We value curiosity, problem-solving ability, and a proactive attitude toward learning
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convert relevant measurement data into actionable information, such as the health condition, and/or the remaining useful life of critical assets. Currently, Artificial Intelligence (AI) based big data
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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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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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Intelligence (also known as Third Wave AI as initially described by DARPA) is the term that references the next foreseen advances within Artificial Intelligence. This stems from the two main styles of AI
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://cheddarhub.org The work is envisioned to have great impact on design and development of intelligent AI/ML orchestration algorithms in real 6G experimentation test beds. The applicant is envisioned to further
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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