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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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analysis of data from a Laboratory Information Management System. Key responsibilities will include: Core Scientific Contribute to the coding and development of custom data analysis algorithms and modelling
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strategies. Carbon-Aware and Sustainable Scheduling Algorithms: Research Focus: Creating algorithms that factor in carbon intensity and renewable energy availability to minimize environmental impact. Skills
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will involve developing deployable prototypes, efficient big data algorithms, and publishing in top-tier venues in databases, machine learning, and data mining. Key responsibilities will include
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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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- your research will result in deployable system prototypes, cutting-edge algorithms, and publications in top-tier venues. You’ll be part of a collaborative environment that values innovation
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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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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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intelligent techniques for scheduling and offloading tasks to the cloud and peer vehicles. This will ultimately meet the Quality of Service (QoS) requirements of time-critical road safety applications and