76 parallel-and-distributed-computing-phd-"Multiple" positions at Cranfield University in United Kingdom
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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access to cutting-edge computational tools and interdisciplinary collaboration. This is a self-funded PhD, open to both UK and international students, offering the opportunity to lead an ambitious project
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD
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. At a glance Application deadline26 Nov 2025 Award type(s)PhD Start date26 Jan 2026 Duration of award3 years EligibilityUK, EU, Rest of world Reference numberCRAN-0003 Entry requirements Applicants
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experience align with the research and training programme, followed by questions from the interview panel. At a glance Application deadline10 Sep 2025 Award type(s)PhD Start date20 Oct 2025 Duration of award4
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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, multidisciplinary PhD research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle
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This PhD project offers a unique opportunity to delve into the complexities of free-market systems and sustainability through a novel ensemble prediction model. With a focus on addressing