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reconstructions of glacier variability for selected areas in Norway. This involves landscape analyses using satellite images before field mapping. The time series will be based upon studies of sediments deposited
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learning-based image classification approaches. The objective is to quantify landscape changes over decadal timescales, with a particular emphasis on Western Norway. Relevant transformations include
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landscape analyses using satellite images before field mapping. The time series will be based upon studies of sediments deposited in glacier-fed distal lakes analysed with ultra-high-resolution scanning
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national and international partners. The PhD project will focus on integrating advanced photogrammetric techniques applied to historical aerial imagery with modern deep learning-based image classification
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live-cell imaging of mitochondria in plants, algae, and marine metazoa with computational analysis to find the universal principles of mitochondrial motion across these species. The project is part of
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measurements, biogeochemical rate modelling, high resolution 3D-imaging, isotope labelling and integrated geobiological data analysis. Analytical approaches implemented can include a multitude of advanced
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understanding through an interdisciplinary approach combining micro-fluidics, with genomics, atomic-scale mineral dissolution measurements, biogeochemical rate modelling, high resolution 3D-imaging, isotope
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techniques include motor/behavioral tests of mice, in vivo compound administration, postmortem tissue harvesting and processing with a focus on the nervous system, cell tracing, immunohistochemistry, mouse
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“Hydrogen storage for maritime and industrial sector.” The position is organized under the Department of Process, Energy, and Environmental Technology and reports to the Head of the Department. The Ph.D
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technology, and ethics. You will be also part of the Digital Signal Processing and Image Analysis (DSB) group in the Department of Informatics at UiO. Francesco Saggio/UiO via Unsplash Francesco Saggio/UiO