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will be modelled by analytical and numerical approaches. Existing analytical approaches will be used as a tool to describe the behaviour of fire exposed TRC in tension, while numerical simulations will
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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; and running regional climate model simulations to project future Greenland surface mass balance under different sea ice scenarios. You will work within a close collaboration between IMAU and AWI
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regions, and may have also been observed in historical trends, but the processes driving this delay are not well understood. This project will use observations and climate model simulations to examine how
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predictive simulations of silicon particle detachment under contact conditions, enabling a quantitative assessment of the governing influence factors and possible mitigation routes to control the detachment
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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REF2029 impact. Methods and workplan Data and simulation: curate multi-fidelity datasets that couple finite-element heat simulations with active thermography experiments. Model design: extend FNOs with
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ecosystems, particularly intertidal and shallow subtidal zones, are highly dynamic and thermally extreme, exposing organisms to both marine (MHW) and atmospheric (AHW) heatwaves, often in rapid succession
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will use a high-fidelity large eddy simulation (LES) code and scientific machine learning tools, such as real-time optimisers, in order to simulate wind farms exposed to various atmospheric inflows. Some
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Application deadline: 31 December 2025 Apply now Are you excited to use data and simulation models to design healthier, more active cities? Join the Institute for Risk Assessment Sciences (IRAS) as a PhD