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necessary to use all epidemiological tools, including microbial genomics, to support this endeavour. This exciting project seeks to using whole genome sequencing measles data to advance the understanding
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overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid
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conducts cutting edge research into discovering new materials for onboard ammonia cracking applications using computational and data approaches. Vision We are seeking PhD student that is motivated by zero
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-mounted ground-penetrating radar (GPR) with smart meter data to transform leak detection. Drones equipped with GPR will identify underground anomalies, while smart meter data will refine localisation
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conducts cutting edge research into discovering new materials for onboard ammonia cracking applications using computational and data approaches. Vision We are seeking PhD student that is motivated by zero
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data sources to answer important population-level questions that will inform health technology assessment, policy, and practice. The successful PhD student will be embedded within an interdisciplinary
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materials. The computer modelling of LSP remains challenging due to its multi-physics and multi-scale nature. The dependency of the process on the shape of the laser pulse, its energy, ablation layers etc. is
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | 3 months ago
the consumption journey. This exciting PhD Programme will look to address these challenges by employing a novel combination of data-donation, data-enhancement, and data-augmented laboratory experiments. The project
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distinct imaging methods to yield a novel imaging method that combines the benefits of both. The aim of this project will be to develop a novel method for fusing the data obtained by x-ray imaging and MIS