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Conditions and Ageing (CC.AGE). Read more about the project: https://www.uib.no/en/sefas About the project/work tasks: The postdoctoral research fellow will perform quantitative data analysis using advanced
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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analysis of ecological or biodiversity data using R. Experience (for example, a master’s project or internship) working with plant, vegetation, or alpine ecology is a requirement. Fieldwork experience and
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hydrological and/or cryospheric modelling, preferably at catchment or regional scales, is a requirement Strong skills in statistical analysis and the handling of large spatiotemporal datasets is a requirement
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. Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C). Familiarity with epigenetics, gene regulation, or chromatin biology. Demonstrated ability to work
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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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with computational analysis to find the universal principles of mitochondrial motion across these species. The project is part of an NFR-funded project “MitoPhyto” combining experimental and modelling
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for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors contribute to severe mental and neuropsychiatric disorders
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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