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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins
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Department/Location: Department of Engineering, Central Cambridge We are seeking a highly motivated Research Assistant/Associate to join EPSRC and industry funded Digital Roads (DR) Prosperity
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Germany, subject to MPIDR terms and conditions. The role is based within the Mortality and Inequalities Research Group at LSHTM with close partnership with the Department of Digital and Computational
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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. You will be able to manage your own research activities independently and will have contributed to academic publications or digital research outputs. You will have excellent communication skills and be
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applications, facilitating the transition of image-based measurement methods from laboratory research to clinical practice. Digital Image Correlation (DIC) is a well-established, non-contact optical technique
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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$116,094 (PhD Enty Level - $108,156) p.a. plus 17% super Innovative suicide prevention research / Leverage digital mental health solutions / Support carers of at-risk youth Apply now to join a cutting-edge
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Living (www.thevivohub.com ) which aims to leverage digital and robotic technologies to support ageing and disabled population in maintaining activity, physical health, and mental well-being
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast