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/thesis: Challenges and opportunities with remote sensing and machine learning in forestry Research subject : Soil science Description: WIFORCE Research School Do you want to contribute to the future
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technology to understand technology's possibilities and its limitations. In our studies of digitization, we move in many contexts such as the public sector, media, games, entertainment, financial companies
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-loss and highly decoupled FR3 (7-24 GHz) arrays, potentially based on three-dimensional elements and classical Huygen source type of element supporting element-specific band-selection filterig will be
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on individual humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in
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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies
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team of over 15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Civil Engineering or a related topic
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totaling 60 ECTS credits) and join an international research team with backgrounds in sociology, political science, network science, statistics, and machine learning. More information on the PhD program can
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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: We are looking for a dedicated candidate who is eager to learn new things and contribute valuable knowledge to society’s work on climate adaptation and the conservation of biodiversity. Applicants