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excellent opportunities to participate in international research networks. We also run an advanced drone lab on behalf of the entire faculty of Mathematics and Natural Sciences (https://www.mn.uio.no/geo
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projects such that the successful candidate will have excellent opportunities to participate in international research networks. We also run an advanced drone lab on behalf of the entire faculty
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: OBJECTIVES | FUNCTIONS Development of an autonomous inspection system for photovoltaic parks based on a drone equipped with an RGB camera and an infrared thermographic camera, including automatic trajectory
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sensing data (satellite, LiDAR, drone or aerial imagery), strong geospatial analytical skills, and proven field and/or laboratory experience in land use change, ecosystem dynamics, biodiversity
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, drone-related measurements, and other field sensing platforms. · Conduct data quality assurance and quality control. · Prepare clean, georeferenced, and well-documented datasets for modelling
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field validation campaigns across diverse HDB precincts and test-bed sites (NUS campus, SIT Punggol Digital District), coordinating sensor deployment, drone-based thermal measurements, and mobile sensing
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sensing data (satellite, LiDAR, drone or aerial imagery), strong geospatial analytical skills, and proven field and/or laboratory experience in land use change, ecosystem dynamics, biodiversity
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environments that aims to address how distributed sensing, fibre-optic monitoring, environmental observations, drone- and satellite-based data, operational infrastructure datasets, and/or machine learning can be
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-atmosphere fluxes of carbon, water, and energy in arctic environments. Observations from eddy flux towers, drones carrying meteorological sensors and gas analyzers, soil sensors, and satellite imagery
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://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Unsupervised Incremental Representation Learning for Ground-Based Drones in Dynamic Industrial