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Field
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Cardiometabolic diseases (CVMD), such as heart disease and type 2 diabetes, represent a major global health burden and exhibit stark ethnic disparities. Current clinical prediction models, even
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3.5-year D.Phil. studentship Project: Computational Fracture Mechanics Supervisors: Prof Emilio Martínez-Pañeda Oxford’s Mechanics of Materials Lab is seeking a PhD (DPhil) student to support the
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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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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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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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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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the most energy‐intensive infrastructures in modern economies, with their demand projected to rise sharply as digitalisation, artificial intelligence (AI), and cloud computing expand. This growth presents
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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