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Field
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optimal ways to schematize and parameterize the subsurface at local to regional scales to assess dike safety using geological and geohydrological data and models, for characteristic fluvial landscapes in
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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characterisation, to generate data-rich descriptions of evolving materials and processing pathways. A central aim is to couple these experiments with machine learning, mechanistic modelling, and automated data
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3rd August 2026 Languages English English English We are looking for a PhD Candidate in Multi-scale, -physics, -fidelity wind modelling for wind farms Apply for this job See advertisement This is
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in predictions derived from medical reports, and on integrating these uncertainties into downstream probabilistic time-to-event models. Applications will focus on prostate cancer, using large-scale
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established, but are sufficiently laborious that making predictions for all but the simplest organic molecules is intractable. This project focuses on nested sampling (NS), a novel 'one shot' sampling method
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PhD Studentship: Bottom-up Decoding of Protein Conformational Landscapes: from Gas-phase to Solution
misfolding-related diseases such as Alzheimer's - but predicting how proteins fold in biological environments remains a key unmet challenge. This project brings together insights from efficient graph-driven
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of flying birds to predict collision risk. This model will be fed by existing empirical data on bird flight behavioural responses to wind turbines from various bird radar studies. This model will allow
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an aerodynamic bird collision avoidance model, combining computational fluid dynamics (CFD) of the flow around wind turbines with the aerodynamic characteristics of flying birds to predict collision risk. This
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statistical modeling with clinical insight, aiming to improve risk prediction and inform sex-specific prevention strategies in atrial fibrillation patients. The research will be conducted in close collaboration