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Field
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composites To propagate uncertainty in material behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help
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, boundary conditions, material anisotropy) into FNO training. Develop an end-to-end pipeline: synthetic and experimental data generation, physics-informed loss functions, uncertainty quantification, and fast
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, uncertainty quantification (UQ) in fields such as climate modelling, nuclear reactor design, and finance often involves models with thousands of variables, posing significant mathematical challenges. Our aim is
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There is scientific uncertainty about how much climate change will occur in future for any given scenario of emissions of greenhouse gases. The reason for most of this uncertainty is that clouds
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extent of domains. Radial Basis Functions (RBF) can be used to infer the boundaries between different domains in a probabilistic framework, thus accounting for uncertainty in the domain definitions
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Is the Job related to staff position within a Research Infrastructure? No Offer Description There is scientific uncertainty about how much climate change will occur in future for any given scenario
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., Superbowl) or large music festivals, assumptions of steady cellular network demand often fail. Sudden surges in GSM/5G traffic, stampede risks, or emergency events introduce uncertainty that challenges
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matches (e.g., Superbowl) or large music festivals, assumptions of steady cellular network demand often fail. Sudden surges in GSM/5G traffic, stampede risks, or emergency events introduce uncertainty
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for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data uncertainty, modality dropout, and noise propagation, which can degrade robustness and
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develops and applies methods for uncertainty quantification, engineering reliability, and risk & decision analysis to support optimal and sustainable decision-making in engineering and environmental systems