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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
knowledge graphs for predictive insights. Design feedback mechanisms to deliver interpretable outputs such as alerts, recommendations, and confidence scores. Validate system robustness using real-world
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We are inviting applications for a fully funded 3.5-year PhD Computer Science studentship at the University of Warwick, jointly supported by GlaxoSmithKline (GSK), to work on an ambitious project
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negative association of inhalation exposure to air pollution, the mechanisms of action to which air pollution impacts lung health are currently unclear. To elucidate this, using a physiologically relevant
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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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student with an aerospace, mechanical engineering, or physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be
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, artificial gauge fields , Artificial Intelligence , Astronomy , Astronomy and Astrophysics , Astroparticle Physics , astrophysics , Astrophysics (astro-ph) , Astrophysics Computational , Astrophysics
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degree (2.1 +/MSc) in mechanical / civil / environmental engineering, physics or a related quantitative field; strong computing skills (Python/MATLAB/GIS); interest in transport or urban futures. Position
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of Mechanical and Aerospace Engineering and is available to UK students. The successful student will receive an annual tax free stipend set at the UKRI amount (£20,780 for 2025/26) and tuition fees will be paid
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HORIZON MSCA COFUND - 13 Fully Funded PhD Positions in Chronic Inflammatory Disease Research: MAP-ID
The Jagiellonian University invites applications for 13 fully funded PhD positions within the MAP-ID (Multilevel Approaches to Understanding Chronic Inflammatory Diseases) program, co-funded by
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simulations, exploring novel aspects of numerical modelling and expanding the computational mechanics capabilities of the group. This project offers the opportunity to join a vibrant research group and