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Field
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insights into the robustness and resilience of land use decisions in an uncertain future. Relevant landscape models will be applied in selected case study countries to explore greenhouse gas flux and
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. The project delves into areas such as hardware-based security measures, tamper detection, and the integration of explainable AI models within embedded platforms. Situated within the esteemed IVHM Centre and
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analysis and there is scope for modelling of the swimmers. The ideal candidate will have a passion for interdisciplinary research at the intersections of physics and biology. Due to the requirements
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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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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