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of surface water, groundwater, and probabilistic seepage analysis, together with modelling and uncertainty assessment techniques. Consideration of these interacting processes may help improve the accuracy and
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-SPOT), enabling probabilistic prediction of contaminant release and evaluation of mitigation strategies. Collectively, the four PhD projects shift drinking water management from reactive monitoring
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at Monash University. The successful candidate will join our world-leading team in Temporal Analytics Lab, a world leading research group uniquely combining research in time series forecasting, classification
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into visions and scenarios for the energy transition Mapping/visualising Indigenous knowledge of climate and weather to support energy forecasting and planning More broadly, applicants are encouraged
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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term