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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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approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
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biodiversity while protecting wheat from one of the greatest biotic threats to production, the wheat rusts. The individual will: (i) visit Bhutan to characterise the spatial distribution and species composition
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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distribution and with synthesised future sea-ice distributions; examine the impacts on barrier wind structure and associated surface turbulent fluxes. Examine the frequency, characteristics and ocean mixed-layer
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. translocations) affect the distribution, and thus impact, of such mutations within endangered populations is limited. Addressing these knowledge gaps is important for realising the potential of genomic data in
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can feed directly into precision surgery algorithms and clinical trials. Few PhD projects offer such a clear line of sight from variant to mechanism to clinical translation. Located on the thriving