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data into clinical impact. They will be responsible for developing algorithms for image analysis, creating predictive models for disease progression, and identifying patterns in imaging data
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research
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group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
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on clusters and high-performance computing infrastructure), Information Retrieval methods, Machine Learning algorithms, wrangling large-scale datasets, and showcasing the research results. The ability to work