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Field
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automated feeders), and analyse microbiome composition using 16S rRNA and whole-genome sequencing. Statistical modelling will test for links between microbes and host development and fitness.� PROJECT
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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knowledge gaps. The project involves both linear and nonlinear dynamics modelling and analysis, as well as experimental testing. An equivalent test structure will first be constructed in the vibration
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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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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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 each other according
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of expressing dementia, particularly those that may not be well understood in typical Western training models. For example, some residents may show signs of distress or confusion in ways shaped by their language
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Josette Camilleri on J.Camilleri@bham.ac.uk for further details on this call. References: Ohlsson E, Galler KM, Widbiller M. A Compilation of Study Models for Dental Pulp Regeneration. Int J Mol Sci. 2022
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this fundamental challenge, the PhD candidate will be part of a wider team to establish methodological framework, combing utilisation of controlled tree growth test, thermodynamic modelling and advanced optical
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will investigate the mechanisms of skeletal muscle disuse atrophy and test strategies to prevent the loss of muscle mass and function. Experimental models of disuse, including limb immobilisation and bed