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. Research will focus on identifying and publishing results in methods to build foundation models, using multimodal and multiscale health data. The role is funded for 24 months in the first instance. About You
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of Surrey, University of Leeds, UKCEH) and Chile (Universidad de Desarrollo and MICROB-R). You will use a system modelling approach to a) quantify available data, b) knowledge gaps and associated risks to c
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-term carbon cycle and over the coming century. This PDRA position will focus on model approaches to quantifying CO2 exchanges associated with chemical weathering associated with the warming cryosphere
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modeling including graphical causal modeling and methodological foundations of the study of technology governance. The research will involve safety cases for AI systems as well as broader aspects of model
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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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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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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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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