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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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will undertake doctoral research focused on activity-based travel behaviour, household energy use, and sustainability policy, contributing to the development of causal inference and agent-based modelling
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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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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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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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results and develop relationships using statistical methods and other analytical approaches such as finite element, and predictive techniques. Application Procedure • A 1-page cover letter, stating
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, and presentation skills • Excellent command of written and spoken English, demonstrated ability in technical writing, including preparation of reports, theses, or scientific publications • Knowledge
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EQUAL OPPORTUNITIES EMPLOYER Please note that an appointment to posts advertised will be dependent on University approval, together with the terms of the employment control framework for the higher
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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