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Field
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position in a ‘landscape of fear’. Objective 3: Develop spatially explicit models to predict how nest footprints combine to generate landscape-level variation in microclimate, carbon flux, and plant
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programming, statistical analysis, or spatial modelling is desirable but not essential. If your first language is not English, you will need to meet the minimum English requirements for the programme, IELTS
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Programming Intelligent Modelling and Analysis Mixed Reality Lab Lab for Uncertainty in Data and Decision Making Visualisation and Computer Graphics Responsible Digital Futures The studentships available
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the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises: An stipend for 3.5 years (currently £20,780 p.a. for 2026/27) in line with UK Research
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confined battery geometries. Advanced modelling—including computational fluid dynamics (CFD) and transient thermal analysis—is required to accurately capture heat flux distributions, temperature uniformity
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Modelling of Weather Impacts: Build machine learning models that analyse these integrated data streams to identify early precursors of weather-induced disruptions. The goal is to forecast turbulence zones
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farms at relatively close proximity can be relevant when considering their annual energy production. This project will examine the uncertainty of various types of numerical models, from fast-computing
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, exerting a transient influence on the landscape and increasing the probability of subsequent and recurrent failures; processes which are currently not accounted for in most landslide susceptibility models
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Learning heat: Physics-Informed Fourier Neural Operators for High-Fidelity Thermal NDE Modern non-destructive evaluation (NDE) increasingly relies on AI models that can reason with physics, scale
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interdisciplinary training, suitable for candidates from biochemistry, molecular biology, computational biology, chemistry, or data science backgrounds. You will gain experience in: Molecular modeling, QM/MM & MD