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have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge of interdisciplinary
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We are pleased to announce PhD studentship project in “Advanced Composites Development for Hyper-velocity Impact Protection of Space Satellites Structures”. This is an exciting PhD research
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. Simulations are suitable to characterise processes in healthy and diseased individuals including stroke patients. Machine learning methods might be considered to accelerate simulations. The project provides a
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
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Machine Learning-based diagnostics and prognostics digital twin system will be developed, aiming to provide fast and reliable predictions of the health of gas turbine engines. Non-confidential operational
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Supervisory Team: Leonardo Aniello, Han Wu PhD Supervisor: Leonardo Aniello Project description: Blockchain and Federated Learning (FL) are two emerging technologies that, when combined, offer a
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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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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics