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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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Project descriptionAutonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents
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research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation
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senior researchers, three postdocs and three PhD students. It is embedded in an interdisciplinary environment where we have close collaboration with other research teams at Chalmers such as technology
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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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on the development of self-sensing fiber-reinforced cementitious composites (SS-FRCMs) for the dual purpose of structural strengthening and real-time health monitoring of infrastructure. The research is structured
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and
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and outside of WiTECH ranging from CMOS over BiCMOS to GaAs and GaN. The research is hosted at Chalmers but will be conducted in close contact to multiple industry experts in communications, sensing
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using state-of-the-art single-cell omics technologies. The team consists of the principal investigator, two experimental scientists (doctoral students), one bioinformatician (postdoc), and one