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Field
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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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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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radar systems. Finally, it will 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
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, and processing conditions influence their behaviour, creating a vast and complex landscape that traditional experimentation cannot navigate efficiently. This project addresses this challenge by bringing
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prevalent noncommunicable disease globally. The confined and complex architecture of the oral cavity, particularly in regions such as dentinal tubules and root canals, makes effective antimicrobial treatment
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: Produce recombinant viral RNAP transcription complexes in insect cells Functionally characterise RNAP activity and validate assay systems Screen fragment libraries using fluorine-based NMR spectroscopy
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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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PhD Studentship: Nanopore Technology for Rapid and Accurate Measurement of Antibiotic Concentrations
the environment and the lack of routine monitoring tools. Current methods for measuring antibiotic concentrations, such as HPLC and mass spectrometry, are expensive and require complex instrumentation, limiting
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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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are invited for a fully-funded Industrial Doctoral Landscape Award, offered in partnership with Rolls-Royce, to tackle key challenges in the design of aeroengine oil systems using multiphase Computational Fluid