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: Develop experimental research and data analysis based on airborne and UAV infrared observations to extract descriptors of fire behavior. Functions to be developed: Process data from airborne campaigns (e.g
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area of expertise for this position is in aeronautics and unmanned aerial vehicles (UAVs) with knowledge of UAV design and system integration, aircraft performance and propulsion, guidance, and
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plan, establish evaluation metrics. Capture and process data (UAV); curation and labeling of datasets. Develop and validate AI/vision models for damage detection and classification. Integrate results in
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submitted in English) and contact details of at least two referees through this form https://www.um.edu.mt/hrmd/workatum-projects by not later than Monday, 12th January 2026. Late applications will not be
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statistical methods in hydrology; - the ability to use hydrological software such as HEC-RAS / HMS is welcome; - the ability to operate unmanned aerial vehicles (UAVs / drones) is welcome; - foreign internships
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of Remote Sensing imagery for land monitoring, from UAV and airborne platforms to imaging spectroscopy, optical to SAR satellite data at a global scale. Increasingly, our work integrates AI and machine
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; -Training and knowledge in Remote Sensing (UAV, LiDAR); - Oral and written fluency in English, oral fluency in portuguese - Excellent teamwork and initiative skills; - Availability to do field work and
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need for reliable and autonomous offshore infrastructure inspection and surveillance. The project integrates unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), and unmanned underwater
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programme Reference Number AE2025-0553 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0553
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sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR as well as small-scale EMI measurements with root and shoot observations in controlled experiments