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validation) of the fluid mechanics of a sample probe washing process in an immunoassay analyser system. The analysis methods will include computational multiphase fluid dynamics modelling, in laminar and
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evaluation and digital implementation phases of this interdisciplinary research project. Operating with a high degree of research independence, the Fellow will clean, manage, and analyse primary quantitative
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, through the advancement of knowledge of soft tissue mechanics and the use of non-invasive imaging techniques. The aim of this project is to create and test biomimetic silicone-MEW valves and optimise
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for the optimisation and development of medical devices, particularly cardiovascular and urological devices, through the advancement of knowledge of soft tissue mechanics and the use of non-invasive imaging techniques
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wave exposure assessments. The post holder will also implement additional advanced monitoring, including tidal, wave, and suspended sediment transport processes at all Irish focal sites within the CMAP
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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to effectively manage many competing demands simultaneously. Please note that Garda vetting and/or an international police clearance check may form part of the selection process. Project Title: Research Fellow for
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and Learning. Project Title: PreciseMed / GREEN TRIALS For an information package including full details of the post, selection criteria and application process see https://ore.ucc.ie/ The University
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including full details of the post, selection criteria and application process see https://ore.ucc.ie/ The University, at its discretion, may undertake to make an additional appointment(s) from