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Recognised Researcher (R2) Positions Postdoc Positions Country Norway Application Deadline 16 Sep 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job
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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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that mitochondria across a diverse range of other species might face the same pressures. This project will explore this hypothesis, combining live-cell imaging of mitochondria in plants, algae, and marine metazoa
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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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Literature. The AI STORIES project is a European Research Council Advanced Grant led by Professor Jill Walker Rettberg, with a team of three postdocs, another doctoral fellow, a research adviser, a data