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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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and mathematics with a good grounding in geophysics, remote sensing and data analysis. Candidates must have a Master’s degree in geophysics, mathematics signal processing or physics, and a PhD in
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and mathematics with a good grounding in geophysics, remote sensing and data analysis. Candidates must have a Master’s degree in geophysics, mathematics signal processing or physics, and a PhD in
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of their fellowship period within the duty component of 25 %. Place of work is Department of Informatics at Blindern, Oslo.. Project description The postdoctoral position is funded by the Department
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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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labelling and integrated geobiological data analysis. Analytical approaches implemented can include a multitude of advanced molecular, microscopically and geochemical techniques and protocols such as
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component corresponding to 30 ECTS, which corresponds to one semester. The remaining six months will be allocated to this formal training. Qualifications and personal qualities: The applicant must hold a
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data—into interpretable spatiotemporal risk models. A key methodological component could be the use of INLA for efficient inference in latent Gaussian models, and the candidate will contribute