5 programming-"Multiple"-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions at Swedish University of Agricultural Sciences
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leading to production and harvesting in the regulated countries moving to unregulated countries. The position is part of a joint research program between Swedish University of Agricultural Sciences (SLU
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Excellent skills in bipartite network analysis Previous research experience in interaction inference Good skills in R programming Experience in preparing and handling large datasets integrating data from
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on forests and forestry as complex socio-ecological systems. We closely collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We
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coast and in offshore areas. The position will also include further development of ongoing data analyses within the national data collection program (DCF), which plays a key role in improving our
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sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation of the ongoing environmental monitoring programs the National Forest Inventory