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to engage fully in the PhD and complete within 3 years For applicants who do not have English as their first language, a recognised English Language qualification is required. How to apply For an informal
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The project: We are recruiting a motivated PhD candidate to work on next generation power electronic modules and converters for Net Zero applications. Renewable energy generation and electric
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Applications are invited for a fully-funded 42-month PhD studentship with Dr Rachel Nicks and Prof Stephen Coombes on the Leverhulme Trust-funded project White Matter Computation: Utilising Axonal
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for your preferred PhD programme must be submitted by 13 January 2025. You must submit your research council funding application by the given deadlines: AHRC North West Consortium Doctoral Training
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application for your preferred PhD programme must be submitted by 13 January 2025. You must submit your research council funding application by the given deadlines: AHRC North West Consortium Doctoral
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PhD Studentship: Open Radio Access Network (ORAN) for Distributed Edge Computing Orchestration in 6G
Overview: Self-funded PhD opportunity in 6G as part of major project hub, further funding possible subject to progress of project and student. Focus on native AI in 6G systems with experimental
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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This 3.5 year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free stipend set at
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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areas. Cranfield is part of the national testbed for 6G, researching in the following areas of interest: Real-time specification of 6G telecommunication and edge computing services using Large Language