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the Cambridge Brain Tumour Imaging laboratory is a unique laboratory involved in using imaging and other techniques o guide and improve surgery. This project is funded through the NIHR HealthTech Research Centre
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of the most resource-intensive processes in this sector is the cleaning of processing equipment, which accounts for around 30% of a site's water and energy use. Cleaning is typically done using automated Clean
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prototype development, construction, operation and analysis as well as characterisation of different scintillators and fibres. This project also includes the opportunity to spend an extended period working
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Generative AI for image and video reconstructions from brain signals DoS Dr Vassilis Cutsuridis (vassilis.cutsuridis@plymouth.ac.uk) 2nd Supervisor Dr. Giorgio Ganis (Giorgio.ganis@plymouth.ac.uk
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change. Thermal imaging captures this process continuously and non-invasively, opening new possibilities for stress research and real-time welfare monitoring. In this project, the PhD student will explore
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, machine learning techniques may be integrated to accelerate simulations and improve medical image processing, ultimately aiding in stroke diagnosis and treatment planning. Please note that this is a self
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allows a user-friendly choice of model (local vs. global), efficient processing of multi-sequence images as well as setting physical constraints (e.g. incompressibility or known fixed points in the setup
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before determining their visual loss arises from cortical, rather than ocular deficits. Tests of cortical visual function are used rarely except by highly specialised neurology/neuro-ophthalmology
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level, DNA2 is implicated in Okazaki fragment processing, DNA double-strand break repair, and the recovery of stalled DNA replication forks (PMID: 33924313). Our previous work has indicated
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging