790 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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/people/nc266.html and here https://www.eng.cam.ac.uk/news/engineering-better-car-experience . Four years funding is provided by the UK's Engineering and Physical Sciences Research Council (EPSRC) and JLR
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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD
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Ovarian cancer is the deadliest of all gynaecological cancers (>2000 deaths/year, UK). It is described as a silent killer as most diagnoses occur after it has spread to the peritoneal cavity (metastasis). It is known that peritoneal cells contribute to the growth of metastatic tumours....
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brings together expertise in health data science, microbial genomics, and cancer bioinformatics. Th selected student will work under the supervision of Dr Arron Lacey, a specialist in machine learning and
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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and establish their potential remain to be answered, both in terms of enabling technologies for distributed sensing and the techniques that exploit it. The focus of the PhD project is to improve our
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more sensitive and faster cancer imaging. This PhD project will focus on surface functionalisation of metascintillators to optimise their scintillation performance, light yield, timing resolution, and