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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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performance under environmental stress. Training in geospatial analysis and ecological modelling will enable predictive insight into urban ecosystem dynamics. You will develop expertise in stakeholder
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extending the existing VL dataset. Design and evaluate DL models capable of classifying marine litter types using multispectral data, with a focus on achieving robustness to varying spectral channel
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contribute to the management and conservation of the commons. Training The PhD candidate will be based at UEA, and, as such, will benefit from the Aries DTP training (e.g. summer and winter schools, ad hoc
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model, human organoid technology, cell and molecular biology, confocal microscopy and metagenomic sequence analysis. By deciphering the interactions between AIEC, the microbiome and the intestinal
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and night-time low temperatures. There is a need to improve the way the stratified boundary layer is represented (parametrized) in these simulations and also interrogate the models with high-quality
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and shape. In recent years, the biological activity of a diverse array of foldamers as potential antimicrobial and antibacterial agents has excited much interest. Despite their antimicrobial properties
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the necessary theoretical tools, using cavity quantum electrodynamic (QED) descriptions, to model and understand this complex interaction between plasmons and molecules, to reveal the necessary procedures
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tools using cavity quantum electrodynamic (QED) descriptions, to model and understand this complex interaction between plasmons in small gaps and the vibrational behaviour of molecules. The student will
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach