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Field
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, prospective plant and soil modellers to contribute to a multi-partner international project ‘Climate-resilient crops with improved phosphorus efficiency through beneficial fungal interactions’. About the Role
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examine how current hydrologic modelling platforms that use Potential Evapotranspiration as an input reproduce observations of evapotranspiration. This role will work with state-of-the-art regional climate
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research project which aims to advance engineering solutions to mitigate the impact of climate change and focus on developing a cost-effective and eco-friendly method for coastal protection and recovery
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anomaly with different weather conditions, which can be used to develop a data-driven model for storm surge prediction. Data Analysis: Process and analyze climate, ocean wave and coastal data to improve
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, machine learning, data-driven dynamics, stability/perturbation theory/rigorous numerics. Possible applications of the new theory include the analysis of spatiotemporal data arising from weather and climate
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, adaptive reuse, heritage, education, digital technologies and community-led environmental transition, creating scalable models with national and international relevance. The post is a critical role, and as
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The Climate Transformation Programme (CTP) aims to develop, inspire and accelerate knowledge-based solutions and educate future leaders to establish the stable climate and environment necessary
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will focus on developing a process-guided and AI-assisted soil community foundation model for natural climate solutions. Candidates with prior experience in process-based modeling/data analytics/deep
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Water Research Centre (EEWRC) The Climate and Atmosphere Research Centre (CARE-C) The Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC) Considerable cross-centre interaction
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research fellow to support ongoing research projects in diffusion generative models and Monte Carlo stochastic simulation methods. This position holder will apply these techniques and other advanced AI