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Field
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-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
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samples. All computational methods and algorithms will be implemented as part of the python based MetaboLabPy platform (https://doi.org/10.3390/metabo15010048 , https://github.com/ludwigc/metabolabpy
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with Rolls-Royce (Enhanced Stipend) Development of Advanced Barrier Coatings for extreme environments Background Applicants are invited
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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GNSS alone leaves systems vulnerable to interference, spoofing, or outages, particularly in dense urban environments. The development of 6G networks with integrated TN and NTN infrastructures provides
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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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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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs