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Topological Data Analysis for Multimodal Neuroimaging: MRI and NIRS Biomarkers of Brain Change DoS Dr Nathan Broomhead (nathan.broomhead@plymouth.ac.uk, tel.: +441752586874) 2nd Supervisor Dr Mariam
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to analyse next-generation spatial transcriptomics data, advancing our understanding of cardiac ageing and disease. Background: Spatial ‘omics methods measure gene or protein expression in their native context
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Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: PhD in ICSA with a start date of 1 September 2026. Applicants should state “Memory Optimisation for Distributed ML Systems” in the ‘Research Topic’ section of the application form, and...
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science research. You will have experience of handling complex survey data at scale. The role holder will support this research using publicly available government and other data (which include NFHS, DHS
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candidates who pay UK/home rate fees. See UKCISA for further information . Starting in October 2026. Later start dates may be possible, please contact Dr Gustavo Carneiro once the deadline passes. You will
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performance degradations and unwarranted system failures can occur. There is certain physical information known a priori in such aerospace platform operations. The main research hypothesis to be tested in
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A large volume of data are routinely captured in high-performance training and competition environments. Whilst these data have the potential to inform key performance decisions, the full potential
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for using data science to address real-world challenges in animal welfare and agricultural sustainability? We are seeking a Research Assistant or Associate in Data Science to join an interdisciplinary
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aid referee decision-making there are many other potential applications for this type of technology and data. The ability to capture the detailed movement of 22 players and officials around the entire
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- See advert for details Deadline: 13 April 2026 Supervisors: Dr Subhash Lakshminarayana (Lead) and Dr Michael Faulkner Safeguarding Power Grid Stability in the Age of Artificial Intelligence (AI) Data