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due to a high Stoke’s shift, and a fast response time. In this project we will develop prototype perovskite scintillator gamma detectors fabricated from perovskite materials grown at Surrey. Perovskite
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or computational frameworks, developed in collaboration with partners with modelling expertise. This PhD offers the opportunity to work at the interface of plant physiology, root biology, imaging and quantitative
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conferences. You will have access to engaging professional development workshops in areas such as research communication, computing and data science, and professional progression through our Early Career
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backgrounds in computer science, physics, signal processing, and statistics. This interdisciplinary environment encourages researchers to pursue their scientific interests with a high degree of intellectual
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. We will host the successful candidate at the Department of Forensic and Neurodevelopmental Sciences (FANS), Institute of Psychiatry, Psychology and Neuroscience (IoPPN) at King’s College London
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techniques in the safety analysis of software components of a new dialysis machine , Science of Computer Programming, Volume-175, 2019, p17-34 [4] MC/DC . Modified Condition/Decision Coverage criterion. [5
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) Research Group and the Department of Mechanical, Materials and Manufacturing Engineering (M3) and within the Faculty of Engineering at the University of Nottingham. The PEMC is a global leader in power
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supervision from an experienced team spanning Manchester Met and Chester Zoo. You will benefit from a skills training programme through our Doctoral College, and will be based in the Faculty of Science and
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, with fixed nuclei, driven by ultra-short XFEL-pulses; • controlling the interplay of single-photon ionization and Auger-Meitner processes, the coupling of electron and nuclear motion, and imaging
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap