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Field
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of physical conditions (pressure, pulse time, temperature) will be investigated, allowing for the design of efficient shockwaves. Essential multi-physics software tools will be developed. The project is a
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, which are essential for safe operation in these challenging aerospace environments. You will develop robust, physics-based models to analyse failure, with a focus on understanding mechanical and
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seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender identities, Black, Asian, or Minority Ethnic backgrounds
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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turbulence, and use this knowledge to identify control strategies through deep reinforcement learning. The methods developed in this project will directly contribute to designing novel porous media
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; Documenting dataset provenance and performing simple quality control checks; Prepare a Zenodo release with FAIR compliant metadata; Draft sections (e.g. “data description” and “technical validation”) of a
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their practical deployment. The Project: This PhD will develop the science and engineering required to overcome these bottlenecks, with the following objectives: • Uncover the mechanisms driving enhanced hydrogen
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uncertainty quantification for robust structural design, particularly for complex aero-engine systems with limited experimental data. Recent work by the University of Southampton developed a novel data driven
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changes (so called swelling). Swollen batteries are at risk of rupturing which may significantly shorten their lifetime. Development of advanced computer models is critical for understanding and
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to identify the material degradation and coatings applications details in extreme environments. A novel techniques/method will be developed with focus on better prediction and more accurate measurement of