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mapping, to rapidly generate linked property-microstructure-chemistry multi-modal datasets, to efficiently produce low‑to‑medium fidelity data streams, which can also be paired to high‑fidelity industrial
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About the Project This project is an exciting opportunity to undertake industrially linked research in partnership with QinetiQ. It is based within the Communications and Electromagnetics research
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the Birmingham MC40 cyclotron facility. This experimental campaign and the new data/insights will allow you to validate structural integrity models of ASSs linking meso- and macro-scales. During this PhD project
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decline later in life, whilst healthier diets, rich in plant polyphenols are linked to reduced risk of dementia. Additionally, the increasing prevalence of stress in our societies is also contributing
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Health emergencies, mass casualty events and disasters generate large volumes of operational, clinical and organisational data. However, these data are rarely synthesised into structured, analysable
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resilient. The PhD student will undertake a full research programme: interviewing participants, leading focus groups, designing studies, analysing data, developing models, designing technological, educational
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. This will provide uniquely high-resolution ground-truth data on particle and flow behaviour within RAM systems, supporting validation of CFD and multiphysics simulations and, where appropriate, training of AI
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interoperability is not solely a technical or procedural challenge, but a socio-technical system property shaped by governance, training, information flows, organisational culture and equity considerations
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There is growing UK and international interest in networked sensing and autonomous collaborative platforms, where multiple airborne sensors co-operate to collect and exploit data. In contrast
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to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative