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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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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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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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Scoliosis (AIS). Although surgery straightens the spine, AIS is associated with poor self-image and psychological distress. This project will investigate this, developing assessment and management tools
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an industry partner which is developing image-based interventions to support people living with dementia. Their interactive platform presents images that serve as prompts for reminiscence, social connection and
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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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imaging and monitoring of resin infusion in sample composite structures to build the digital twin and then explore methods for defect prediction and real time process control. The improved process
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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
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and technology. Desirable (not essential): Research experience in sports medicine and technology (e.g. publication or final year project). Programming skills in MATLAB or Python. Application Procedure
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head