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plumes. Emissions plumes from high-altitude sources (e.g. aircraft) can persist for weeks or even months in the stratosphere, but most global atmospheric models are unable to preserve such fine structure
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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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About us The Social Computation and Representation Lab (SoCR Lab; www.socrlab.net) uses mathematical models and causal experimental designs to understand the fundamental rules behind human and AI
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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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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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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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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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