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for analysing authentic, synthetic, and manipulated images or videos. The work will combine predictive performance with explainability, uncertainty estimation, robustness, and generalization. Attention will be
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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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3rd August 2026 Languages English English English We are looking for a PhD Candidate in Measuring Uncertainty and Risk with Agentic AI for Decision-Oriented Modelling Apply for this job See
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-dimensional data. Develop modular methods that incorporate domain-specific information into latent-variable models. Investigate methodological questions related to computation, identifiability, uncertainty
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on computational models that are inherently uncertain. Uncertainty quantification (UQ) seeks to characterize and propagate this uncertainty but translating it into actionable risk measures remains computationally
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that relates diagrams to composition temperature, pressure, synthesis, processing and uncertainty? The PhD candidate will develop and evaluate large language models (LLMs) assisted methods for extracting
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-dimensional data. Develop modular methods that incorporate domain-specific information into latent-variable models. Investigate methodological questions related to computation, identifiability, uncertainty
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
in yards, creating opportunities for more data-driven planning. AI can replace or supplement traditional planning approaches, which struggles to manage the uncertainty and variability that are inherent
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within the CREST-GLOBAL research team, which focuses on equitable urban transitions and decision-making under uncertainty, in close interaction with the Department of Design. Are you motivated to take a
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complexity, fault susceptibility, countermeasure effectiveness, robustness across devices and operating conditions, reproducibility, and the uncertainty and confidence associated with security conclusions