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-based hail climatology for France, Switzerland and Northern Italy, including hail swaths per event across more than a decade. Design, develop and train geostationary satellite-based hail algorithms using
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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postdoctoral researcher with: A PhD (or near completion) in Computer Science, Computational Biology, Mathematics, Bioinformatics, or a related discipline. Proven expertise in machine learning and algorithm
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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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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learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
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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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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation