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’ or ‘internationally excellent’. The highly research active SP Section comprises 13 permanent academic staff with research interests in Bayesian computational statistics and machine learning, uncertainty quantification
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to revolutionise performance, making ASHPs more effective and efficient in variable climates, targeting a minimum 20% improvement in Coefficient of Performance and a 50% reduction in defrost cycle frequency. You
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optimisation and capability development, equipment maintenance and troubleshooting, data acquisition and analysis, setting and achieving EHS&Q objectives and targets, and driving continuous improvements
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required to provide regular reports on expenditure against budget and outcomes achieved against targets. An annual report is also required by the funder NIHR. The role is required to work closely with Theme