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emphasis on emerging wearable optically pumped magnetometer (OPM) technology. These methods and hardware will improve the spatial resolution, robustness, and computational foundations of MEG source imaging
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. The project combines quantitative modelling of markets and the wider energy system with empirical analysis of how flexibility is created, priced, and traded by market participants. A central objective is to
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the cognitive neuroscience of language, multilingualism and spatial cognition, including entorhinal cortex based spatial grids and cognitive maps. The ideal candidate holds a degree in Biomedical Engineering
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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | about 1 month ago
LevelMaster Degree or equivalent Skills/Qualifications Master's degree in Geography or related fields; Enrollment in a PhD programme in Geography or related fields; Experience in GIS, Spatial Modelling, and
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processing of sequence data, phylogenomic analysis, GIS-based spatial analysis, and comparative macroevolutionary analysis. Attend local and/or international conferences for the purpose of presenting research
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efforts, such as the collection and analysis of biodiversity data. See https://www.youtube.com/watch?v=cIw3PekWDRM for an insight into what we have done previously and what the fieldwork can involve. The
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students as needed. Where to apply Website https://www.academictransfer.com/en/jobs/362841/doctoral-candidate-spatial-inte… Requirements Specific Requirements An MSc in physics, meteorology, hydrology
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abundances by pathogen, time period, or region (curves, heatmaps), and spatialization of detections (Leaflet, Folium) for comparing multiple wastewater treatment plants. • Analysis of transmission flows
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use strategies to conserve fish and wildlife habitat while meeting human needs. Teaching responsibilities will include an undergraduate course in remote sensing and spatial data analysis and a graduate
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interdisciplinary collaboration. Faculty and students conduct innovative research in Bayesian methods, causal inference, data science, machine learning, statistical genetics, longitudinal and survival analysis, and