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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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, predictive maintenance algorithms, and digital twin technologies tailored specifically for healthcare, aviation, and sanitation industries. You will identify critical operational pain points within
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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context. The work will include, but is not limited to: investigating new mathematical formulations of the underlying physics; developing fast algorithms and numerical methods that leverage modern parallel
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve