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datasets with different configurations (e.g., number of channels, sampling frequency and resolution). To leverage large-scale self-supervised learning to train models on unlabeled EEG data, reducing reliance
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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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degraded ecosystems across different habitat types. This is important for establishing the extent to which ecoacoustic methods and metrics are transferrable between places. There is scope within this project
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provide a full-time PhD stipend to enable doctoral research that aims to make a difference to survival outcomes for out-of-hospital cardiac arrest (OHCA). The exact PhD topic is negotiable. Whilst it must