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Field
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for individuals with a strong interest in artificial intelligence, machine learning, process systems engineering, and pharmaceutical manufacturing. The expected outcomes will contribute to more resilient
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations
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for doctoral students. Overview This PhD project focuses on developing real-world deployable Machine Learning (ML) solutions integrated into Industrial Internet of Things (IoT) edge devices for condition
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. The research will combine computational modelling, experimental validation, and machine learning techniques to develop a predictive phenomenological PAC model. The successful applicant will develop and apply
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approaches (e.g. SPG) as well as the use of machine learning, advanced computing, statistical modelling to explore the stochastic response to complex scenarios. This project offers the opportunity to undertake
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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The University of Exeter and Oxford Instruments Plasma Technologies are offering a jointly funded PhD position in computational and machine learning modelling of low temperature plasmas. Oxford
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these challenges by combining advanced metrology, data science, and machine learning to develop predictive models and new standards for recycled plastics. Based at the University of Manchester, in collaboration with
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical