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, and Resilience—CMT investigates long-term environmental changes, seasonal dynamics, extreme events, and strategies for sustainable mountain management. The centre collaborates closely with stakeholders
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://www.uib.no/en/sefas About the project/work tasks: The postdoctoral research fellow will perform quantitative data analysis using advanced techniques such as signal processing and dynamic systems modeling, and
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communities that depend on them. Through four interconnected research themes—Trends, Seasonality, Extremes, and Resilience—CMT investigates long-term environmental changes, seasonal dynamics, extreme events
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-temporal dynamics of plague (Yersinia pestis), the bacterium which caused the Black Death followed by several waves of plague outbreak among people in Europe - a disease which during the Black Death killed
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specialization in signal processing, bioinformatics, simulation/visualization, or dynamic systems, or have the doctoral thesis submitted prior to the application deadline. It is a condition of employment that
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, Extremes, and Resilience—CMT investigates long-term environmental changes, seasonal dynamics, extreme events, and strategies for sustainable mountain management. The centre collaborates closely with
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what extent simpler models (possibly based on machine learning) can be integrated into full-physics simulation. The successful candidate will contribute to research activities in the CSSR centre, and in
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strengthen the Department in subjects related to alluvial fan sedimentology, architecture, and petrography. The position will focus on developing new concepts in catchment–alluvial fan dynamics within a
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carbon sinks dynamically evolve under climate change. The postdoc will work on improving and applying the land surface model CLM (Community Land Model) that is used in the Norwegian Earth System Model
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an aim of developing a decision-making toolbox for optimization of logistics network using optimization and/or simulation methods and software Support the rest of the team wrt methodology and