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This PhD project will investigate the recent field of study of Causal Machine Learning, which aims to modify and augment Machine Learning by using Causal Analysis techniques as a way to solve its
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automated security systems that can detect and respond to dangers in real-time. With this opportunity, you will explore into cutting-edge technologies such as artificial intelligence, machine learning, and
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flow of realistic car shapes and their implications on pollutant dispersion under actual road conditions. Overview The PhD student will test these two hypotheses: There is a strong effect of the vehicle
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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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experimentation and validation, and machine learning. References of our current/recent work are here: "Automatic Retrieval-Augmented Generation of 6G Network Specifications for Use Cases," IEEE Communications
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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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from such machines to derive algorithms expressing their state of health and next maintenance needs. A background in both engineering and machine learning would be useful, although help is readily
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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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Cranfield’s Advanced Vehicle Engineering Centre is inviting applications to study for a PhD in battery modelling and management for electric vehicles. Several projects are on offer, covering