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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering
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the behaviour of energetic materials both at the microscopic (i.e. crystal deformation and failure) and macroscopic levels. Numerical techniques for the generation of digital twins and modelling
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, computational modelling and experimental work. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in turbomachinery pump development, hydrogen
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-preserving learning methods • Experience working with diverse user groups and participatory design methods Attributes and Behaviours • Excellent communication skills, both written and verbal • Ability
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project offers a unique opportunity to develop a cutting-edge genomic epidemiology toolkit for real-time fungal surveillance. You’ll optimize DNA extraction protocols using advanced enzyme-based methods
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materials manufacturing, characterisation and testing equipment. Flexible and hybrid working is supported. Receipt of a competitive, tax-free stipend. Numerous opportunities for local and international
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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appropriate media and methods. Communicate complex information orally and in writing to a range of stakeholders including those who might not be familiar with the work. Attend and present research findings and
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environmental degradation and economic strain. Existing detection methods fail to address the issue effectively, being both costly and unreliable. This project proposes an innovative solution by integrating drone