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Field
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Plants and trees are vital to the UK’s economy, ecosystems, and climate goals, providing an estimated £15.7 billion annually in environmental and economic value and playing a crucial role in
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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for research staff (contract type: open-ended contract; job category: PhD junior researcher) to collaborate with the funded line of research “Biological Systems Modelling and Applied Marine Ecology
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, device modelling/simulation aspects of new tunnelling devices. By using dedicated electrical dc and RF measurement equipment within our measurement & test centre, you will develop and carefully analyse
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the construction of a unified data model for Data Spaces that facilitates adoption by stakeholders involved in the socio-economic ecosystem. In addition, the design of a federated algorithm that allows decision
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science interlink prevention and prediction of wildfire risk, by contributing to the development of a fundamental physical model to understand the process of fire spread for wildfires, as part of a European
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qualities required for such purposes. Digital terrain models will be used to efficiently map cultural remains under forest canopies. The second project (Mapping Natural Forests in Norway) focuses on mapping
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detection mechanisms for those plants to which they have become adapted, to select suitable plants for feeding or for laying their eggs. We will use the model system of the cabbage white butterflies, Pieris
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 2 months ago
models as predictive tools to address questions regarding the response of deep-sea ecosystems to various pressures. A key question addresses the best combination of ML and network analysis to maximize