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manufacturing (year 1) - Advanced Composites manufacturing using energy absorbing fibres and nanomaterials (year 1) - Analytical/mathematical modelling and FEA modelling of hyper-velocity impact test of
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of work as a case study, this PhD will contribute new knowledge to the fields of archival and performance research, generating a model of practice that can be utilised by other artists. Structured over
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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to date by validating numerical models against test data, before undertaking parametric studies to investigate the sensitivity of the key variables that affect the flexural performance of composite steel
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive
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the formation rates or composition of a biominerals from known environmental conditions. This project aims to construct such a model. The ultimate goal is to create a general framework for predicting
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complementary methodologies (corpus data and offline experimental measures). On the theoretical side, the project will develop a formal compositional model that generates the observed parameters of variation and
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. You enjoy combining experimental laboratory work with theoretical analysis and modelling. While your main focus will be the research project and your own development as a researcher, the position also
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of the data. Our response to climate change will change the composition of air pollution factors children and adolescents are exposed to. Many air pollutants are expected to reduce, but some may increase
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challenge-driven with a systems-based approach and requires interdisciplinary efforts, which is reflected in our team's composition spanning engineering, natural and social sciences. It is a dynamic and