68 high-performance-quantum-computing "https:" "Simons Foundation" positions at Cranfield University
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the EU Research Framework Programme? Not funded by a EU programme Reference Number 5263 Is the Job related to staff position within a Research Infrastructure? No Offer Description Faculty of Engineering
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potential progression up to £71,050 per annum About the Role This role is responsible for leading and delivering communications across a complex change programme, ensuring colleagues are clearly informed
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
to cutting-edge facilities including High-velocity impact testing, Advanced composite manufacturing labs, X-ray computed tomography and High-performance computing resources for AI model training This project
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programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking
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AI-electronic systems, ensuring secure communication and operation. Side-Channel Attack Mitigation: Implement techniques to protect systems against side-channel attacks, safeguarding sensitive
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the EU Research Framework Programme? Not funded by a EU programme Reference Number 5270 Is the Job related to staff position within a Research Infrastructure? No Offer Description Faculty of Engineering
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Programme? Not funded by a EU programme Reference Number 5293 Is the Job related to staff position within a Research Infrastructure? No Offer Description Faculty of Engineering and Applied Sciences
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profoundly affect their mechanical properties and overall performance. Therefore, understanding the temperature field and developing effective thermal control techniques are vital to ensuring a high-quality WA
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Programme? Not funded by a EU programme Reference Number 5286 Is the Job related to staff position within a Research Infrastructure? No Offer Description Faculty of Engineering and Applied Sciences
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the computational inefficiencies of physics-based models and enabling faster, potentially more accurate predictions. However, AI models require substantial volumes of high-quality, labelled training data, which