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Change, University of Exeter The University of Exeter invites applications for a PhD studentship in geospatial ecology starting from April 2026 onwards. The student will join the Terrestrial Ecosystem
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will apply nonlinear and associational (colloquially called “causal”) timeseries analysis techniques to provide a more rigorous, and more statistically significant framework for understanding
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areas, could include deep learning (e.g. Long Short Term Memory - LSTM), statistical baselines (e.g. Autoregressive Integrated Moving Average - ARIMA, Kalman filters) and transformers (e.g., spatio
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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climate models, including the UK Earth System Model (UKESM), resulting in critical gaps in both seasonal forecasts and long-term climate projections. This PhD will develop a new parameterisation of snow
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to other indicators of unrest, such as seismicity. This PhD project will drive innovation in modelling magma-mush processes and the generated surface deformation and seismicity during unrest episodes
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opportunity to devise an exciting research project, to receive training in data capture and manipulation, statistics, trait analysis, and modelling of interaction webs, and to undertake fieldwork
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billions of consumer devices relying on accurate positioning daily. Improving GNSS accuracy, especially for low-cost, mass-market receivers, therefore has significant economic and societal impact. However
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future climate change affect these hazards? The PhD researcher will have scope to determine: Selection of study rivers/locations; hazard focus (river migration by bank erosion or avulsion); methodological
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and collaborative partnerships. They will receive interdisciplinary training across microbiology, statistics, as well as working with policy stakeholders to translate research into real-world