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(Master / PhD / Postdoc). Our expertise lies in quantum foundations, quantum information theory and quantum technologies. For additional information, please visit: https://dakic.univie.ac.at/ . Your future
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) under the supervision of Dr Elton Santos, and Dr Nina-Juliane Steinke. This is a joint programme between both institutions, which combine advanced modelling methods (spin dynamics, quantum approaches, AI
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via joint activities with EU and UK cybersecurity hubs, preparing you for careers in trusted electronics, AI security, and national critical infrastructure protection. Graduates from this programme will
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Scottish Power as part of your program. The project Power Electronic Devices (PEDs) have been proposed as a new approach to increase the uptake of low-carbon technologies (such as electric vehicles and heat
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the opportunity to undertake a placement within Scottish Power as part of your program. The project Power Electronic Devices (PEDs) have been proposed as a new approach to increase the uptake of low-carbon
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative
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About the project: Supervisor: Professor Nicholas Hine, University of Warwick This project uses cutting-edge computational and machine learning methods to accelerate catalyst discovery for fuel cell
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to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
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integration. About This PhD This PhD programme is part of a prestigious £8M EPSRC Programme Grant on Advanced Integrated Motor Drives (AIMD), a major research initiative launched in 2025. You will work on the
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Project Overview This is an opportunity to conduct fully funded interdisciplinary research under the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex