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Field
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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propagate through bacterial communities while deactivating AMR genes. However, current designs are limited by scalability and complexity. This project aims to overcome these limitations by integrating large
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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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benefit from world-leading infrastructure uniquely suited to support the programme, i.e. a fully operational network of Commercial-off-the-Shelf (COTS) primary surveillance radars specially modified
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to complex geometries, and run in real time for digital-twin monitoring. This project will develop physics-informed Fourier Neural Operators (FNOs) for thermal NDE of curved and layered composite structures
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this goal. However, the computational expense of these models limits their use for generating forecasts, constraining the spatial resolution, level of physical complexity, and number of ensemble members
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science including: * Algorithmic game theory * Approximation algorithms * Automata and formal languages * Combinatorics and graph algorithms * Computational complexity * Logic and games * Online and dynamic
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affect over 50 million people worldwide, with limited therapeutic options and enormous societal costs. The endosomal sorting complexes required for transport (ESCRT) system represents a convergence point