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PhD-studentship in Applied Mathematics / Quantitative Ecology: Wind‑Assisted Dispersal of Insect Tree Pests: An Interdisciplinary Modelling and Ecological Study Award Summary 100% home fees covered
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to taxonomic and ecological groupings. The development and exploration of models that integrate biological understanding with atmospheric dispersion models to predict spatio-temporal spread of wind-dispersed
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in conjunction with the industry partner, this PhD project aims to develop a reliable numerical modelling framework capable of: (i) simulating coupled heat and fluid flow within deep geothermal
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research, including: pre-clinical mouse models of cancer multi-parameter flow cytometry and immune phenotyping histology, immunofluorescence and spatial tissue profiling cell culture and molecular analysis
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field of multiphase flow modelling. Contact Dr Nadimi (sadegh.nadimi-shahraki@ncl.ac.uk) for more information. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4 Years Application Closing
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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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, including weather, cyberattacks, and equipment degradation, are unpredictable, causing AI behaviors to deviate from lab-tested performance. Current digital twin technologies focus on predictive maintenance
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differential equations and boundary conditions describing heat and fluid flow will be embedded directly into the learning process to constrain model training and reduce data requirements. Time- and space
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the development of a multi-layer hydrodynamic model capable of representing key three-dimensional flow processes in riverine and estuarine systems. This model will be coupled with advection–diffusion–reaction