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evaluation of North Atlantic jet-stream changes in large numbers of state-of-the-science global climate model simulations that have recently been produced by key inter/national projects, using the latest
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and glacier models, based on large ensembles of simulations extending to 2300. The simulations will be from two international projects aiming to inform the Intergovernmental Panel on Climate Change
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’ (PHOENIX), led by Associate Professor Thomas Aubry (University of Oxford). Using a combination of laboratory experiments, field work and numerical modelling, PHOENIX aims to improve our understanding
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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split 0.5FTE on the UKRI Medical Research Council funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations in healthcare ; and 0.5FTE on the Health Service Modelling Associates (HSMA
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blades. In this role you will: Design, build and optimise optical and inductive thermal NDE rigs for curved, metre‑scale blade sections; Develop and validate forward–inverse heat‑transfer models
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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: ‘Understanding how land-use-climate interactions restructure terrestrial biodiversity to develop a new generation of global biodiversity models’, commencing in early Autumn 2025. This Research Project is being
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modelling, simulation, and data analysis, applied first and foremost to the field of platelet biology and haemostasis. The postholder will play a key role in a project that will develop novel computational