19 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"FEUP" PhD positions at University of Nottingham in United Kingdom
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The School of Computer Science at the University of Nottingham is pleased to invite applications for a fully funded PhD studentship in deployable, efficient, and trustworthy computer vision. This is
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resolution. This PhD offers the opportunity to conduct cutting-edge research with direct industrial impact, combining fundamental fluid mechanics with modern data-driven techniques. The successful candidate
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in advanced experimental techniques, data analysis, and interdisciplinary problem solving at the interface of physics, materials science, and device-relevant functionality. Outcomes will include high
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for fuel system applications. While these methods provide a wealth of knowledge and information, they remain impractical for industrial use. Therefore, AI modelling techniques will be harnessed to develop
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Studentship Information Supervisor: Vinay Shukla Subject Area: Plant & Crop Science Research Title: Root oxygen dynamics and development Research Description: The student will be part of a
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology
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strategy to improve the turbulence detection and quantification. The flow turbulence and velocity in a vascular flow phantom will be measured by Particle Image Velocimetry (PIV), against which MRI data will
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MEng degree in Electrical and Electronics Engineering or Aerospace Engineering. To apply or for further information, please contact Dr Sharmila Sumsurooah Sharmila.Sumsurooah@nottingham.ac.uk Funding
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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support population-level prevention strategies. Further information: Applicants should have either a minimum 2.1 undergraduate degree in a relevant area (public health, epidemiology, economics, statistics