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primarily use existing datasets in close collaboration with the project Past, Present, Future for the Alpine (PPF-Alpine, https://mountainsinmotion.w.uib.no/ ), but there is also flexibility for the candidate
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you want to take part in shaping the future? PhD position About the positiWe are offering a fully funded 3-year PhD position within a multidisciplinary research project aimed at improving the safety
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attitudes. Do you want to take part in shaping the future? ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) PhD position About the positiWe
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. Experience with epidemiology and statistical analysis, including the use of statistical software such as STATA, R, or SAS, will be viewed positively. Documented or demonstrated ability to work independently
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on both meroplankton and benthos data to enhance the value and efficiency of long term time series analysis. The position is based in Bodø and will be available from January 2026. via Unsplash Qualification
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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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language (written and spoken) is considered an advantage. Please refer to documentation requirements. Experience with epidemiology and statistical analysis, including the use of statistical software such as
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-modal spectroscopy (e.g., UV–Vis, NMR, EPR and complementary methods) to characterize metal coordination, redox states, and catalytic intermediates. You will work closely with colleagues spanning protein
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Computational Geosciences and Modelling at the NORCE Energy and Technology Department in Bergen. About the position The position is part of the Norwegian Research Council funded centre for environmentally
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security, aiding conservation and informing management policy. You will use advanced novel genomic approaches to assemble, annotate and explore the genome biology of a non-invasive and one of the most