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accountably. This is where you come in. Your mission Working at the intersection of privacy research and real-world engineering, you'll design and build a computational stewardship engine—an autonomous agent
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screened without further cumbersome purification. These methods will allow the parallel synthesis and testing of ca. 100 compounds in a single operation, potentially taking less than a week to design
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UKRI rate). Overview This PhD aims to improve risk assessment and mitigation of high-impact and damaging weather events by developing catastrophe model methods, and adjustment factors to address current
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emergency responders. By combining global landslide data, innovative machine‑learning methods, and new ways of representing runout, the research will produce faster and more reliable nowcasts for use
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programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and interdisciplinary systemic thinking for Net Zero. The ReNU+ vision is that they will
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‑related pathways, long‑distance wind‑borne dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne
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dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne dispersal risk for a range of pests of concern to GB
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of £20,780 (2025/26 UKRI rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Overview ReNU+ is a unique and ambitious programme
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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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pressures from climate change, urbanisation and ageing infrastructure. Although high-fidelity numerical models can simulate hydrodynamic and pollutant transport processes, their computational cost limits