352 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" PhD positions in United Kingdom
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Field
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supporting the setup, calibration, and running of laboratory experiments, including the preparation and configuration of sensors, data acquisition systems, and associated hardware and software components
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reusable plaque–flow atlas. Key objectives include to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric
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formed during late-stage deglaciation and subsequent marine transgression. These data will provide critical constraints for palaeoclimatic reconstructions and help quantify the magnitude and style
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establishing events and aiding future design improvements. Currently, there remains a paucity of data in this domain, making it difficult to identify any notable trends and associated failure mechanisms
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data-driven methods to develop an inverse design framework for manufacturing systems. Together, we will advance the capability to design manufacturing systems that embed reliability, resilience
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manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website . Entry requirements: A 1st or high 2:1 degree in computer science, manufacturing/industrial engineering, data
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to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric archetypes (e.g. curved vessels, bifurcations, side branches
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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a
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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
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cloud data centres. However, this can come at the cost of performance and slower function processing, which manifests as higher energy consumption and increased operational costs (OpEx) for operators. So