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of the intense rainfall that causes these floods, forecasts still show significant uncertainties, even for very short forecast horizons (of less than 6 hours). This PhD project aims to study how these forecast
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generation and pressure evolution. Our approach will combine physical insight with data-driven techniques and uncertainty quantification, offering fast, reliable predictions and contributing to safer, longer
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, develop connectivity analysis techniques for dynamic brain PET data and explore artificial intelligence solutions to improve brain PET quantification. As a PhD candidate, you will contribute
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Mediterranean farmland: Setting conservation thresholds and targets using keystone small mammals (COMPETE2030-FEDER-00730000), funded by the ERDF through the COMPETE 2030 Program. Where to apply Website https
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project Can AI interpret graphs like a human materials scientist that relates diagrams to composition temperature, pressure, synthesis, processing and uncertainty? The PhD candidate will develop and
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because they enable learners to monitor their own understanding, recognize uncertainty, detect errors, and regulate their behavior accordingly. The PhD project will examine how metacognitive monitoring and
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properties of the fault zone, or processes driven by fluids and chemical reactions. The ultimate goal is to reduce uncertainty regarding the presence, geometry, and dynamics of hydrogen-generating zones, and
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grid reinforcements, heat networks and local flexibility, but privacy law (GDPR), commercial sensitivity and regulatory uncertainty keep this data locked away. Hence, critical infrastructure decisions
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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scenarios with additional events that fill gaps in the existing dataset of scenarios, incorporate non‑linear effects such as failure of regional flood defences, and account for uncertainty in breach growth