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About the ProjectProject details: Next-generation networks are rapidly outscaling the capabilities of traditional management paradigms. While early AI/ML models offered a degree of automation, they
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habitat fragmentation. Working at the forefront of ecological modelling and movement ecology, you will build next-generation, process-based models to predict how real populations respond to complex
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Number of Opportunities Available 1 fully funded place Department Centre for Doctoral Training in the Modelling of Heterogeneous Materials (HetSys), Department of Physics About the project: Bottom
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workflows rely heavily on geometric de-featuring, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and
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skills, which will be required to lead the development of automated data analysis and modelling. The student will also undertake a research secondment to coral reef monitoring sites at NEOM for three
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restoration success and flood resilience elsewhere. Current models treat sites in isolation, lacking tools to predict these feedbacks. This three-year PhD will develop and apply cutting-edge numerical modelling
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contribute to pioneering computational tools that extend far beyond potassium. About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling
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early as the advert may be removed before the deadline. High-dimensional computations are ubiquitous in science and engineering, often arising from models with numerous parameters. For instance
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conventional analysis methods struggle. The work is inherently interdisciplinary, combining elements of experimental NMR, chemical kinetics, mathematical modelling, and computational data analysis, and the
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-Zhang (KPZ) universality class is a collection of models that includes the random growth of a surface over time or the behaviour of a large number of particles that move around in space and interact with