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of data but in many cases, are failing to use this data effectively. ‘Bad’ data carries significant costs for organisations and the wider economy, as well as having a negative environmental impact. This PhD
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holistic views of complex chemical and biological systems. However, discrepancies in data structure, measurement scales, and resolution across platforms make this integration challenging. Existing approaches
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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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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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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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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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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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