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Field
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all, the traditional statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental
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Evaluating the role of Big Data and satellite technologies in understanding livestock impacts on the upland landscape DoS: Dr Mark Whiteside 2nd Supervisor: Dr Katherine Herborn 3rd Supervisor: Dr
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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the effectiveness of anticipatory cash transfers in response to climate disasters, using large-scale RCTs in Bangladesh and other countries. It investigates how early interventions can mitigate the impacts of extreme
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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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correlation structures across data modalities that relate to outcomes such as survival and treatment response. Validation & Benchmarking: Apply the framework across cancer types, evaluating various foundation
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This large-scale ecological project investigates the barriers and drivers of post-fire forest recovery. With climate change and the spread of forest fires to new areas, it is important to
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) out to 2050. Tasks include compiling big-data inputs, developing CNOSSOS-EU compliant simulations, validating predictions with field/lab measurements and mapping future hot-spots. Ideal profile: honours
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and colleagues located across the 4 nations of the UK. HDR UK’s mission is to unite the UK’s health data to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and