35 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Cranfield University
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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, computer vision or flow measurement background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience of computer coding in some form or any discipline is also
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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 PhD project will investigate the recent field of study of Causal Machine Learning, which aims to modify and augment Machine Learning by using Causal Analysis techniques as a way to solve its
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studentship is part of the Connected Waters Leverhulme Doctoral Programme, which is funding up to 18 PhD studentships to conduct multidisciplinary research on freshwater ecosystems, across two universities
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part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active
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the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement
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existing experience. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning
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This is a self-funded opportunity relying on Computational Fluid Dynamics (CFD) and wind tunnel testing to further the design of porous airfoils with superior aerodynamic efficiency. Building
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training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement with partners and stakeholders and inclusion of student-led activities