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Field
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source, has implications for heat network demand and electricity network demand. To model the implications of widespread adoption of new technologies, requires new demand profiles which these networks will
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. The resulting dataset will be analysed using Structural Equation Modelling (SEM) to quantify the relationships between these factors and uncover both direct and indirect pathways affecting behaviours
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their entire life cycle due to the variations arising from geometry, material properties and loads during the long-term operation. This leads to a growing need in model identification, calibration, and
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University of Strathclyde will lead the wind energy training and research elements of the programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area
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emissions and are being implemented to provide a carbon efficiency assessment of farm enterprises. The contribution and management of ensiling at the farm scale to these models has not been fully explored
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. Experimental studies will be performed in wind tunnels with advanced measurement techniques with high spatial and temporal resolutions. Realistic car models (DrivAer models) will be considered in this study and
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fine-scale, fully distributed hydrological modelling, with the ultimate goal of optimising NFM strategies in moorland, to improve flood resilience for rural, upland communities. The studentship will be
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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generation of experts to challenge the cutting-edge of computational modelling in diverse, heterogeneous systems. These systems span a wide range of exciting research areas, including nanoscale devices
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding