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processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS
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of research experience; OR master's degree and two (2) years of research experience. Preferred Qualifications: Ph.D. in Geography, Environmental Sciences and Engineering or equivalent with emphasis on remote
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, and will work in close collaboration with the FOX team of the CRISTAL laboratory. The LOA team has internationally recognized expertise in the field of radiative transfer and remote sensing. The CRISTAL
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, Geoscience, Remote Sensing, Hydrology, Data Science, Physics, or related fields • Experience in machine learning (ML), artificial intelligence (AI) or related fields • Software skills in ML languages such as
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and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil Engineering & Geosciences. Conditions of employment
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research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic
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, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
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Job Purpose The successful candidate will contribute to a project focusing on remote RF Sensing and its applications in healthcare involving technologies for both sensing and communications, under
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Master’s degree in machine learning, computer science, or a forest-related field with a focus on remote sensing Experience with deep learning The following experiences and skills will be emphasized