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Field
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Programme Overview This PhD is part of the Engineering Hydrogen NetZero (EnerHy) Centre for Doctoral Training (CDT), a newly established EPSRC-funded initiative focused on advancing research and
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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models to predict defect behavior without the computational cost of DFT. The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent at Bachelors or Masters level in
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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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-modal datasets. It will use advanced analytical models to generate evidence about new and existing inflammatory pathways and how these will impact the progression of dementia. The PhD (DPhil) programme
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will be an advantage if candidates have an interest in optimisation, control and computing systems, model checking, mathematical logic and good programming skills, ideally in MATLAB, Python and/or C/C
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Samuele Lo Piano, samuele.lo.piano@pg.edu.pl , Politechnica Gdanska s.lopiano@reading.ac.uk , University of Reading Project description: Optical radiative transfer models (e.g. canopy reflectance models