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Field
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, which are essential for safe operation in these challenging aerospace environments. You will develop robust, physics-based models to analyse failure, with a focus on understanding mechanical and
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will also include evaluating and validating existing numerical models, ensuring their reliability in predicting real-world conditions. This project is supported by brand-new laboratory facilities
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skills include: Interest or background in composite materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a
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learning’ approaches (such as Deep CNN’s) and ‘unsupervised learning’ approaches (such as reinforcement based learning and generative adversarial networks). Some of the main problems with Second Wave AI
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materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a plus Familiarity with FE simulation tools such as ANSYS
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comprehensive model of what tranquillity is, the factors that influence it and how to design for it. Attention to design contexts and design processes will be key to ensuring that useful measurements, methods and
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The Project: Are you passionate about materials science, numerical modelling and materials characterisation techniques? Do you want to work on cutting-edge research that will directly impact nuclear
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health management (IVHM) system that leads to enhance safety, reliability, maintainability and readiness. Generally, prognostics models can be broadly categorised into experience-based models, data-driven
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identifying a novel biomarker for early decline in the heart-brain-axis, this study aims to explore the effect of alpha-synucleinopathy in heart and stellate ganglia. Using a PD animal model with a neuronal
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such as SHACL (Shapes Constraint Language), the NCT3TA reference model, and standards like HISO 100xx and ISO/IEC 11179-xx. Prior experience with these tools is not required—training will be provided