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investigates the thermodynamic modelling of chloride migration in concrete exposed to accelerated chloride ingress conditions, with particular focus on replicating and predicting the results of the NT Build 492
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socio-marine ecosystem models Marine and coastal socio-ecosystems such as Dublin Bay are highly complex systems subject to accelerated climate change. They are characterised by interacting biological
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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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enables the fabrication of spatially complex metal structures with features on the micron-scale. However, our capacity to intelligently design these surfaces is 2 limited, because the models that predict
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PhD studentship on developing a living lab digital twin to integrate catchment models and climate adaptation measures for catchment management in Ireland. This PhD is part of a larger interdisciplinary
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competitiveness assessment. The main tasks will be to develop models to assess life cycle cost, environmental and social impacts of mushroom production to evaluate mushroom sector sustainability. Supervision
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models of mushroom farming. This project aims to support the transition towards technology adoption in the mushroom sector through an environmental, social and competitiveness assessment. The main tasks
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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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-biorefinery LCA model (LCAD2.0 ) to evaluate the environmental sustainability of various feed, food, material and energy value chains derived from grass. They will explore these value chains under various scale