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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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(IoT) device ecosystem. Despite the technology’s potential, however, flexible electronics face numerous technology challenges. This PhD project aims to tackle one of the most critical technology
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to explore these projects and the results coming from them, the latter involving the modelling and follow-up of any high probability events. The student will also explore the most promising methods
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statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
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breast cancer in animal models (4). In this PhD project, we will investigate: The effect of combined treatment with ITCs and a selected anti-cancer drug (sorafenib or triptolide) on breast cancer will be
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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hepatic dysfunction in Alpers’ syndrome. The proposed studentship will involve a multi-disciplinary mechanistic approach harnessing induced pluripotent stem cell (iPSC) in vitro models and a unique resource
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the preparation of articles for publication in scientific journal(s) Good numerical and statistics skills and familiarity with text editing software, such as Word, Excel, etc. Knowledge of advanced statistical
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operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
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deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of