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with deep learning and 3D point clouds Apply for this job See advertisement About the position The Faculty of Environmental Sciences and Natural Resources Management (MINA) at Norwegian University
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computer vision models for forest-based 3D point cloud data. In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek
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have resided in Norway or carried out their main activity (work or study) there for more than 12 months in the 36 months immediately prior to the recruitment date. Selection process Application process
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project. Applicants must indicate which Digi-thematic area(s) the project relates to in the application letter, as well as one or more preferred supervisors. This must be confirmed in a Letter of
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continuously and precisely sense and process molecular signals among infectious bacteria colonies for diagnosis. The receiver development will consider novel design principles combining approaches in biosensors
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provide insights into developing a receiver system that can continuously and precisely sense and process molecular signals among infectious bacteria colonies for diagnosis. The receiver development will
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results. You will join the Section for renewable energy and forest sciences and conduct cutting‑edge research using remotely sensed point‑cloud and image data to map forests. The position is part of two
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. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load
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a procedure for obtaining refugee status under the Geneva Convention 140 are not taken into account. Exclusivity The candidate must be working exclusively for the action. Selection process Recruitment
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methods in forestry generate vast quantities of data and demand more accurate information. Machine learning allows for the systematization and processing of this data into new forms of information