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materials and we utilise these non-absorbed X-rays to massively increase image contrast and reduce radiation exposure using coherent synchrotron radiation. We have developed these “phase contrast” and “dark
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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark
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optical fields. The successful candidate will work on designing and analysing protocols that exploit quantum-optical channels-such as those encountered in coherent and incoherent spectroscopy To be
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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analysing protocols that exploit quantum-optical channels-such as those encountered in coherent and incoherent spectroscopy To be successful in this position, you'll have / you'll have as a minimum: Evidence
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optical fields. The successful candidate will work on designing and analysing protocols that exploit quantum-optical channels-such as those encountered in coherent and incoherent spectroscopy To be
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on designing and analysing protocols that exploit quantum-optical channels—such as those encountered in coherent and incoherent spectroscopy To be successful in this position, you’ll have / you’ll have as a
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analysing protocols that exploit quantum-optical channels-such as those encountered in coherent and incoherent spectroscopy To be successful in this position, you'll have / you'll have as a minimum: Evidence
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possess translational symmetry, the role of structure and symmetry in glasses is not established. This research programme involves the development of new x-ray and electron diffraction-based methods
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I supervise computational projects in electron microscopy imaging for investigating materials at atomic resolution. Some projects centre on analysing experimental data acquired by experimental