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such as micro-XRF, synchrotron diffraction, SIMS, and 3D X-ray CT, it will reveal how variations in composition, microstructure, and metal-making processes shape an object's unique metal pedigree
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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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of objects (”curved”, ”pink”, ”having eyes”, “being animate”, ”having agency”, or ones that are hard to name) that are crucial for our everyday functioning. This research is only possible now thanks to 1
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to further optimisation, etc. The project objectives are to: Develop a detailed understanding of current hydraulic modelling practice. Create a new framework to quantitatively assess and rank different
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adaptive strategies while combined theoretical and empirical approaches enhance wellbeing and reduce carbon emissions. Project objectives Construct AI algorithms employing advanced thermodynamic and machine
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transitions in chiral drugs, enabling direct determination of crystal structures at the sub-micron scale. Specifically, we will address two key objectives: (i) probing solid-phase transitions of chiral drugs in
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this PhD, synchrotron X-ray diffraction will be used to track the evolving crystallography in steel samples over a wide range of cooling rates and isothermal dwells. The diffraction data will be interpreted