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to study corrosion, cracking and mechanical degradation, develop advanced computational models using modern C++ and high-performance computing to simulate material behaviour over a 100+ year timespan. This
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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nicola.love@ukhsa.gov.uk . To be considered for this PhD please send a copy of your CV and a personal statement up to 500 words explaining your suitability and experience to-date to nicola.love@ukhsa.gov.uk
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heavier than their fossil fuel powered counterparts. A framework that can accurately model complex dynamics and generate projections for future scenarios is essential for understanding the impact of changes
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for specific questions. For more information about the School of Computing, please click here To apply, please complete an online application and upload a plain text copy of your CV (2 pages) and covering letter
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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season properties (e.g. number, intensity) for lead times ranging from one to approximately six months in the latest generation of dynamical seasonal and decadal forecast models. Seasonal forecasts
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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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language, a copy of your English language qualification if completed must be uploaded. Contact Details For further details, please contact: Professor John Sayer Translational and Clinical Research Institute