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Field
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large data set? We are offering a unique opportunity to drive the development, capture and iterative improvement of both a large data set model, and the techniques to generate informative report-based
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of Manchester. The post holder will be responsible for leading on the analysis of routinely collected social care data, using sophisticated multivariable modelling techniques to determine whether reablement
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outcomes over time using multi-state models, accounting for association amongst processes and across time. The role will involve both theoretical and computational model development, together
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University of Surrey. You will be working on a 3-year project (funded by Innovate UK) looking at coupling of fluid and solid models and how we could use AI to speed up the computational time required. You will
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iterative improvement of both a large data set model, and the techniques to generate informative report-based outputs. About the Role Your role will contribute to the data capture, recording and iterative
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the development of new anchoring technologies for floating offshore wind turbines. Your role will focus primarily on the development of simplified computational models, and you will contribute
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aerodynamic models and aircraft design development. Within the Department of Aeronautics and Astronautics, you will be based in the Aerodynamics and Flight Mechanics research group comprised of experts in
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materials characterization tools; computational multi-physics/electromagnetics modelling and eigenmode analysis for photonic crystals; terahertz far-field spectra measurements or near-field scanning
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involve the analysis of VOCs and low-molecular weight compounds in breath samples collected from two model study systems along the continuum of mammal diving abilities - elite freediving humans, and grey
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University of Surrey. You will be working on a 3-year project (funded by Innovate UK) looking at coupling of fluid and solid models and how we could use AI to speed up the computational time required. You will