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to study the effects of altered gas and pressure on the human brain. The studentship will start on 01 April 2026. This collaborative project is based at the University of Plymouth’s Brain Research & Imaging
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digital signal and image processing, IoT, cyber security, deep learning, and software systems. Applications in healthcare, multimedia, and sustainable urban environments are encouraged. School
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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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organizational levels of the brain – from molecular and cellular processes to complex neuronal networks and behavior. In association with the SFB 1436, Neural Resources of Cognition (supported by the German
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of biological processes using diverse experimental systems. We apply state-of-the-art technologies, including high-resolution fluorescence microscopy, quantitative proteomics (HDX and XL MS), (cryo-)electron
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-related transport phenomena all require precise knowledge of fluid flow dynamics. Advanced experimental methods such as Particle Image Velocimetry (PIV) and 3D Lagrangian Particle Tracking (LPT) provide
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model characterisation strategies definition of the necessary equipment definition of the necessary processing algorithms Implementation/validation/drafting of scientific articles in collaboration with
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: environmental monitoring, AI, computer vision or multispectral imaging. Entry Requirements At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5
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to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing
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of maturity, this technology requires to experiment a change of paradigm to guarantee a sustainable development for the years to come. One pathway to achieve this paradigm shift relies on the development