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team members to examine patients’ responses by analysing EEG and behavioural data. Candidates are expected to hold a medical qualification (MBBS or equivalent) and be fully registered with the GMC, have
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measurements and in the underlying physical models. Machine learning (ML) techniques can be exploited to identify common patterns in the data and augment the physical laws of wave propagation, leading in turn
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cutting-edge data from new ground and space-based facilities to address fundamental questions in galaxy evolution? Then this might be the right opportunity for you. The Astronomy Group within the School
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research on this topic. Projects have been designed to generate tangible outputs such as published papers, software or data sets within a 12-month period. The fellowship should not be viewed as an
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will also work alongside other team members to examine patients’ responses by analysing EEG and behavioural data. Candidates are expected to hold a medical qualification (MBBS or equivalent) and be fully
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-quality, repeatable data. Develop and apply signal processing workflows for weak transient signals, long-term monitoring, feature extraction and statistical analysis. Support sound playback/stimulation
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for finalists. Candidates should submit with their application contact information for two to three references from experts at the ladder faculty ranks or highly accomplished senior researchers from corporations
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to submit the names and contact information for at least two (or up to three) references. We encourage candidates to apply by March 2, 2026, but will continue to review applications for up to 30 days from
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undertake qualitative fieldwork to understand perspectives of groups experiencing digital inequalities. You will coordinate evaluation activities, lead data collection and data analysis, prepare project
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from developing the conceptual frameworks and instruments to data collection and analysis. You will further support and engage with academic and non-academic partners in the UK and Europe in conducting