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, Computer Science, Electronics Engineering or equivalent. Experience in one or more of the following areas: machine learning, deep learning, software-hardware co-design, computer system performance, design
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Machine Learning. You can find out more about the potential content that these might include here . There will also be opportunities to contribute to the development of associated new MSc programmes in
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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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transferring learning from other geographic regions and data types, machine learning methods, Bayesian inference and interrogation theory. The post may involve travel to Iceland and Italy in support of your work
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datasets, performing statistical analyses and machine learning approaches to identify biomarkers of treatment responses. The candidate will also develop and implement bioinformatics pipelines in a high
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statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing to the development of biomarkers and predictive models. A critical part of your
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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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requires a high-degree of team work and interdisciplinary activities. What You Will Do: Perform research in machine learning methods based on control theory applied to problems in neuroscience. Prepare write
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implementing the Grade 11 module of ICCS, examining civic learning among older adolescents, particularly in vocational education pathways. You will engage in international comparative research, applying advanced
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual