49 phd-in-computational-mechanics-"Prof"-"Prof" PhD positions at Cranfield University
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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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experience align with the research and training programme, followed by questions from the interview panel. At a glance Application deadline28 May 2025 Award type(s)PhD Start date29 Sep 2025 Duration of award4
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We are pleased to announce PhD studentship project in “Advanced Composites Development for Hyper-velocity Impact Protection of Space Satellites Structures”. This is an exciting PhD research
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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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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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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack of representative failure models for gear failures causes difficulties in their useful lifetime...
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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...
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised