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inventory; analysing spatial data obtained during fieldwork; creating data visualisations, predictive models and advanced data analyses based on results of analyses of different types of findings; assisting
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), which studies coastal dynamics and sea-level variability across multiple spatial and temporal scales, using laboratory and field experiments, remote sensing, and numerical modelling. The team aims
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towns and cities as flood peaks, known as Natural Flood Management (NFM). Most research on NFM centered on hydrological modelling and its effectiveness in reducing flood peaks at varying spatial scales
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Building engineer or Environmental Science, Planning, Engineering, computer science, innovation science or related fields with demonstrable experience in spatial analysis and numerical modelling
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include developing foundation models for genome interpretation; creating methods for multi-omic and spatial data analysis and integration with phenotypic and clinical data; and advancing AI-based frameworks
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of environmental seismology, an emerging field focused on interpreting seismic signals generated by surface processes. This interdisciplinary PhD project aims to integrate hydraulic measurements, physical models and
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and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities
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references.. The Michigan Neuroscience Institute is an inclusive workplace that encourages individuals from diverse backgrounds and with diverse experiences to apply. Please visit: https://medicine.umich.edu
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and spatial omics integration and latent modeling with scVI for batch correction and label transfer Regulatory genomics and motif analysis using tools from MEME Suite or HOMER. Cloud-native NGS workflow
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transport companies, taxis and other sources of mobility. Development of data-driven predictive models. Analysis of the spatial and temporal variation of transport services and their demand. Analysis