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This studentship is open to both UK and International applications. This is a self funded PhD opportunity. Find out more about tuition fees. Cranfield Doctoral Network Research students at Cranfield benefit from
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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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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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, 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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the research findings to the broader aviation community, through publications, conferences, and workshops, to accelerate the adoption of these optical measurement capabilities for future system development
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. This PhD research aims to define novel approaches to developing and combining these intelligences, utilizing both 1st and 2nd wave AI approaches, in the context of Defence applications. Such applications
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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A funded PhD studentship is available within the Autonomous and Cyber Physical Systems Centre at Cranfield University, Bedfordshire, UK. As aerospace platforms go through their service life, gradual
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Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality....
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital image correlation is an effective tool to characterize material properties. The analysis of the images...