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will involve a combination of longitudinal, descriptive, and cross-sectional studies to better understand the bidirectional influence of training and match-demands of tier 3 football during
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models of the additive manufacturing process. Surrogate models to accelerate virtual material testing and verification will be developed to allow the generation of property distributions from process
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an objective and consistent method of measurement. The implication of this is a mechanism through which customer and supplier can agree on model quality. Furthermore, the outcome will inform the development
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. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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Nuffield Department of Clinical Neurosciences (NDCN), MRC Brain Network Dynamics Unit, Mansfield Road, Oxford The post holder will develop computational models of learning processes in cortical
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will develop novel tools which will allow efficient flow modelling tools for other researchers to explore higher fidelity thermochemistry modelling. The main responsibilities of the post will be
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, the successful applicant may contribute to areas including, but not limited to: Spatio temporal modelling and forecasting (e.g., epidemic dynamics, population-level health trends, video reconstruction) Robust and
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functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids