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should have a thorough understanding of respiratory immunology and particularly eosinophilic and T2 immune pathways including mast cell, Th2, ILC2 and epithelial related processes in asthma. It is expected
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge engineering, linked data, web technologies. About the role
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at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are
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Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level
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of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted
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, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates
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qualitative work package which aims to understand multi-stakeholder perspectives of the C(E)TR process and how this may be improved. This will include participant recruitment through various means, data
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environment for the pursuit of cutting-edge cardiovascular and metabolic research. We study the fundamental molecular, cellular, and physiological processes that underly normal and abnormal cardiovascular and