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is seeking a PhD student to join an ongoing Royal Society–Research Ireland University Research Fellowship project focused on Machine Learning for the Design of Additively Manufactured Two-Phase Heat
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of the role is to provide Trinity students with academic learning services and to equip them with world-class academic and graduate skills for their studies and beyond. A key component of the role is to work
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-doctoral Researcher position in advanced nanofabrication and ultrathin membrane processing. The post is funded by an industry partner (Lace Lithography) and will be employed through Trinity College Dublin
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the Teaching and Learning IT Team, overseeing software deployment and system administration for computer labs and BYOD environments in E3LF, and secondarily across campus and remotely. They will manage and
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activities in the School of Medicine and to support the Director of Postgraduate Teaching & Learning, Associate Directors and the Postgraduate Manager. This is a full-time permanent role in Ireland. We require
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catalysts used in chemical processes. The successful candidate will combine state-of-the-art quantum chemical modelling alongside machine learning techniques and contribute to the development of predictive
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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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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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machine-learning models to investigate how brain, environment and social factors influence cognition, ageing and neurodegenerative disease. The role will contribute primarily to WP6 and related analytical