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will be mapped throughout development and the fate of different tissues tracked through the milling process. The University of Reading boasts excellent molecular, imaging and analytical laboratories as
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knowledge of human brain function and to use this knowledge to help people with psychiatric and neurological disorders. Our research integrates multimodal brain imaging techniques with novel neuromodulation
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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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this project, using extensive primary cell culture, molecular analysis, scRNAseq, non-invasive imaging analysis, along with mechanistic studies using 2D/3D culture models, we will dissect the distinct cellular
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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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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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the piles will be recorded using thermocouples attached to data loggers. A small-scale prototype involving geothermal loops 2 will also be installed within a number of these foundation piles which will be
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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