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) About the Project Unravelling the outcomes of cell–cell interactions is fundamental to understanding biological processes. The ability to visualise and track these interactions in vivo greatly enhances
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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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: 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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power consumption. Many emerging biomedical devices, such as non-invasive and indwelling systems, require reliable operation and continuous feedback on biochemical conditions at the device–tissue
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speed - Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace
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operators in a cycle of designing bespoke, inflexible models. Large Language Models (LLMs) represent a paradigm shift, offering a path to a more sustainable and intelligent approach. Their emergent
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students Subject areas Computer sciences Physical & Environmental Sciences Project description The accelerating impacts of climate change—particularly those related to water, such as flooding, coastal
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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new types of measurements, can help us create a more complete picture of the electron wavefunction. The project relies on a combination of concepts from quantum mechanics, information theory, and