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well as emerging wireless technologies, such as reconfigurable intelligent surfaces and metasurfaces, holographic MIMO, or near-field communication, will find this project particularly well-aligned. Strong
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. Bayesian networks and related machine-learning methods will be used to calculate cross-section probability density functions in a much faster way, enabling the combination of multiple probability
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tax-free stipend aligned with UKRI rates (£20,780 for 2025–26). The award supports 3.5 years of full-time study starting 1 October 2026. Deadline 5 January 2026 Enquiries Contact Dr Joanna Moss
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are welcome to contact Dr Roman Bauer for informal enquiries and further information about the project. Funding Funded in competition with multiple projects. Funding is for 3.5 years. Funded by EPSRC and co