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of advanced computational techniques. This research will integrate power system modelling, optimisation algorithms, and artificial intelligence (AI) techniques to develop an innovative framework for strategic
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motion capture data collection involving patients would be advantageous, as would experience with musculoskeletal modelling software. Candidates with experience in clinical practice relating to human
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Photovoltaic Modelling for Performance Optimisation Theme 3: AI-Enhanced Coordination of Renewable Energy for Smarter Grid Management Theme 4: Decoding Social Acceptance: The Community Lens on Large-Scale Solar
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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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About the Role Join a multi-disciplinary team that explores human intestinal development and disease using cutting edge single cell and spatial biology technologies, organoid models and
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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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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