41 phd-computer-science-fully-funded-"IMPRS-ML"-"IMPRS-ML" PhD positions at Cranfield University in United Kingdom
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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future hydrogen fuel cell powered aircraft. Join our diverse and inclusive team to transform the future of aviation as part of the Centre for Propulsion and Thermal Power Engineering. Offering fully funded
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full
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, building resilience and long-term sustainability. This fully funded PhD includes an enhanced stipend of £25,726 per year, undertaking an international placement, and completing a bespoke training programme
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Cranfield University invites applications for a PhD funded by Thames Water through the Ofwat Innovation Fund. The studentship covers full Home tuition fees plus a tax free stipend of £24,000 per
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aircraft. While working on this exciting research project, you will be provided with: A fully funded 4 year full-time PhD - £24,000 tax-free stipend per year. Attendance/presentations to international and
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing