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is essential for robust climate prediction and mitigation strategies. The tropical Atlantic is a pivotal region in the global methane cycle, where both methane sources and sinks are influenced by
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to predict coastal wetland restoration success. Successful candidate will first construct sensors using microcontrollers (e.g., Arduinos and peripheral sensors). These sensors will be designed to measure key
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of waterlogged conditions, peatlands are projected to be particularly impacted by future climate change, through changes in both temperature and precipitation. Bioclimatic envelope models predict significant loss
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effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
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human behaviour, influenced by people’s social connections, and resources. Predicting disease spread is difficult due to factors like parent’s age, ethnicity, socioeconomic status, and nursery layout
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. This PhD project aims to predict what these gigantic waves look like when they appear in the middle of the ocean, where many nonlinear effects take place, such as Benjamin-Feir Instability, spreading
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models to predict defect behavior without the computational cost of DFT. The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent at Bachelors or Masters level in
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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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conservation targets. The student will use advanced modelling techniques to predict how different solar park configurations could balance biodiversity gains with the practicalities of land-use and energy
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UKHSA surveillance datasets to see if OTC sales can be used to monitor GI infection activity and better predict outbreaks. The PhD offers the unique opportunity to develop skills in analytical