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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 28 days ago
sensors # Investigate gas dispersion in different zones of the flotation cell by determining bubble size distributions (e.g., using optical probes) and/or by applying ultrafast X-ray tomography (e.g., ROFEX
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within the scope of the Multiannual Funding of R&D Units 2025-2029, with the reference UID/00048/2025 (https://doi.org/10.54499/UID/00048/2025 ), funded by national funds through the Portuguese Foundation
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. Your main responsibilities will include: Fly drones and process data of multispectral, thermal and LiDAR sensors Implement approaches to integrate drone data into an existing agroecosystem data
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Collaborate with the research group and external partners on cutting-edge atomic and nuclear sensor applications Present research findings at group meetings, conferences, and through scientific publications
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, writing publications, and disseminating results. - ROS 2 environment and robotics simulators. - Integration of simulated sensors (vision, sonar, LiDAR, inertial navigation). - Implementation of guidance
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radiation, and soil moisture. As an Environmental Monitoring Technician I (Temporary), you will: Pour concrete/install corral panels Install sensors and station equipment Wire sensors and station equipment
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. Currently, SAIL is conducting multiple projects ranging from Hybrid Aerial Underwater Robotic System (HAUCS)– a cyber physical system (CPS) for aquaculture, to sensors and platforms for maritime applications
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at KTH Royal Institute of Technology is seeking a highly motivated doctoral student with a strong background and interest in spatial AI, navigation, sensor fusion, optimal estimation, and machine learning
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ground or aerial platforms Sensor-integrated cyber-physical systems Automation for crop monitoring, input application, and field operations Human-technology interaction and system reliability in
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decision support Analysis of large-scale geospatial, sensor, and remote sensing datasets (e.g., multispectral, hyperspectral, LiDAR) Predictive modeling for crop performance, resource efficiency, and climate