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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with Rolls-Royce (Enhanced Stipend) Development of Advanced Barrier Coatings for extreme environments Background Applicants are invited
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of DTU Engineering Technology and the Department of Electric Energy at the Norwegian University of Science and Technology (NTNU). The project will investigate coordinated operation and control of local
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation of process
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The successful candidate will join the young, vibrant, and interdisciplinary FINATRAX Research Group, which builds bridges between electricity markets and digital technologies in Luxembourg
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Application process Send your application in English by email to amx@wzw.tum.de with title “Research Associate application” at latest 01.07.2025 including • A cover letter (for example elaborating your
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time: climate change and digitalisation. With a high standard of excellence, we are working to make a...
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Location: UK Other Background Applicants are invited to undertake a 4-year, enhanced stipend PhD studentship, within the Digital Metal CDT digitalmetal-cdt.ac.uk at the University of Nottingham
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applicants will be contacted directly. Contact Prof Ben White with any questions about the project, or hdr@qut.edu.au with any questions about the application process. About the scholarship QUT is offering
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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