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proposal is not required, instead upload a copy of the project name as a word file. For queries regarding the application process, please contact pgr.sst.enquire@citystgeorges.ac.uk City, University
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performance of AI models for fall detection. The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis
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partners. They will develop advanced skills in experimental hydrodynamics, materials characterisation and computational simulation – highly sought after in the UK’s growing offshore energy sector
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, materials characterisation and computational simulation – highly sought after in the UK’s growing offshore energy sector. This research will directly contribute to more reliable, cost-effective and
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, and flexible working arrangements ideal for computational and field-integrated PhD research. Methodology You will develop a process-based, spatially explicit population model for European amphibians
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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that corrected pseudoranges correspond to physically consistent receiver positions across all satellites. Temporal smoothness: enforcing corrections that are consistent with expected receiver dynamics, such as
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methods to enable efficient structural simulation of novel aircraft configurations – essential as aviation transitions to alternative fuels. These methods will also expand the role of simulation in
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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includes participatory design workshops, simulation-based testing, and opportunities to publish in leading journals. Join our inclusive doctoral community and benefit from advanced training