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behaviours of thin foils in vacuum and inert environments will be explored. Based on the results, a constitutive material model including the creep effect (time, temperature and load dependencies) will be
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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constitutive material model including the creep effect (time, temperature and load dependencies) will be developed. This project is available from 1st October 2025. Applications accepted until post is filled
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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electronic health records, explore health usage related to HIV, TB, HBV and HCV for migrants to the UK. • adapt existing health economic models to estimate the cost-effectiveness of alternative infection
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advantageous. Familiarity with mathematical modelling of power electronics circuits is also desirable. Funding Further information and other funding options . Informal Enquiries: s.neira@ed.ac.uk
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and use the results to iteratively refine devices and models. You should have the ambition to publish you work in top ranked international journals and at leading conferences and have a dedication to
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either of these species is likely to affect its onward behaviour, and data on these processes will support predictive modelling. The PhD student will be a part of the Surrey/AWE Centre of Excellence in
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modelling tools, depending on your profile, to unlock – and inform the design of – disruptive solar technologies. You will be expected to undertake some project management activities, supervise multi
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spectroscopy and HPLC), organic synthesis, electrochemistry, hydrogel soft matter and modelling. You will be mentored by Dr. Maguire and will learn how to design and manage projects, how to conduct research, how