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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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-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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life, gradual performance degradations and unwarranted system failures can occur. There is certain physical information known a priori in such aerospace platform operations. The main research hypothesis
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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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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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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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June 2025 or as early as possible thereafter. This is an exciting opportunity for an enthusiastic Astronomical Data Scientist to work within the Cambridge Centre of Excellence in Astronomical Data
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forecast local generation and demand. To do so, historic local data (e.g., the active buildings in Swansea University) and Met Office data will be used to train and validate the proposed ML model
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of multiple long-term conditions resulting in increased risk of hospitalisations, polypharmacy and/or mortality using population-scale, linked, electronic health records from the Secure Anonymised Information