264 network-coding-"Chung-Ang-University"-"Chung-Ang-University" PhD positions in United Kingdom
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at Harper Adams, meaning everyone, including staff, students and industry partners, benefits from a close network of knowledge and opportunity exchange. Situated in Shropshire, the campus and the surrounding
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at Harper Adams, meaning everyone, including staff, students and industry partners, benefits from a close network of knowledge and opportunity exchange. Situated in Shropshire, the campus and the surrounding
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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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the evidence–base needed to understand the impact on health, to inform public policy, and to develop potential mitigation strategies. Traditionally, this information has come from ground monitoring networks
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challenge in the UK's Net Zero transition. Current satellite dependent navigation remains vulnerable to interference, jamming and signal degradation, causing serious problems for safe and efficient transport
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Project summary: A transition to net zero is desirable overall, but its costs and benefits are unevenly distributed across time, space, and between individuals, and policy to implement it must be
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD
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methods experience. Quantitative applicants are expected to have worked with large datasets or equivalent project experiences, and have programming skills such as R coding (preferable) and communication
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debris (Kessler's Syndrome). To manage this, global sensor networks monitor our space environment in both optical and radio regimes. This research project will contribute to advancing space situational
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multispectral and/or SAR data to improve biomass recovery estimations, measuring biases between GEDI and EO time-series estimations, developing customised hybrid neural networks (e.g., CNN-LSTM for capturing both