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16th November 2025 Languages English Norsk Bokmål English English Postdoc - AI in forestry Apply for this job See advertisement Key Information At SmartForest (www.smartforest.no), a center for
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Council (ERC Advanced Grant, 101199790). More information about the project can be found here . We are looking for candidates whose research falls within one or more of the following areas: Plato´s
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-agent systems, mathematical modelling, formal verification methods, stability metrics, agentic AI and data analytics are an advantage. Experience with large datasets, real-time systems, and integration
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digital twins that simulate and predict nitrogen use efficiency (NUE) in forage grasses and oats. By combining high-resolution phenotyping data from the TraitFinder system, drones, and robotic sensors with
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages. The LEAD AI mobility rules must be followed. Outgoing fellowships require
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the divide between big data and educational theory. British Journal of Educational Technology, 54(5), 1095-1124. Swist, T., Gulson, K. N., Benn, C., Kitto, K., Knight, S., & Zhang, V. (2024). A technical
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work upon. Suggested reading to explore this line of research further: Kitto, K., Hicks, B., & Buckingham Shum, S. (2023). Using causal models to bridge the divide between big data and educational theory
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., Hicks, B., & Buckingham Shum, S. (2023). Using causal models to bridge the divide between big data and educational theory. British Journal of Educational Technology, 54(5), 1095-1124. Swist, T., Gulson, K