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Field
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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through both academic and non-academic channels The project is multidisciplinary and in the project you will join a large team of researchers from different universities and disciplines. For this reason it
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: Masters and subsequent PhD in Physics, Chemistry, Material Science or related disciplines Experience in neutron spectroscopy, e.g. INS, QENS, NSE Good knowledge of the structural characterization of matter
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We are seeking a Postdoctoral Researcher in Geospatial Urban Big Data to support the analysis of urban dynamics and decision-making in territorial planning. The candidate must be proficient in GIS
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with the Principal Investigator Professor Cormac Sreenan and the gVID project Technical Lead. A suitable candidate will have a PhD, 8 years of research/industrial experience and a keen interest in
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. They will also help coordinate and implement future field campaigns to fill key field data gaps. Additionally, the successful candidate will be responsible for advancing cutting-edge methods for quantifying
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involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in understanding the drivers
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans. Analyzes complex sensor data, works with a multidisciplinary team to develop health digital
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with the goal of understanding how inflammatory processes intersect with