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of Oxford. The post is funded by United Kingdom Research and Innovation (UKRI) and is for 24 months. The researcher will develop 3D mapping and reconstruction algorithms with relevance to mobile robotics
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at any research group connected to the Nano Area of Advance at Chalmers. You find the full list of PIs of these research groups on the Chalmers homepage: https://www.chalmers.se/en/collaborate-with-us
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, sensor-driven prognosis, and complementary supervision. These secondments form an integral part of your training and will contribute significantly to the interdisciplinary and intersectoral nature of your
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. Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic/socioeconomic data) Co-designing tools and analyses with municipal and MPO clients, including
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into large-scale O&M practices. ETH Zürich (Switzerland), supporting academic collaboration in SHM data processing, sensor-driven prognosis, and complementary supervision. These secondments form an integral
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of fully autonomous navigation systems. Main responsibilities Develop and optimize autonomous navigation algorithms for outdoor mobile robots. Integrate and fuse data from perceptual sensors (LiDAR, RGB
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 13 hours ago
. Recent updates to QFED include integration of fire products from new sensors (VIIRS), and a new multispectral approach for retrieving fire radiative power (FRP) for two phases of burning: flaming and
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The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en/offerta-formativa/dottorato/2025/computer-science About the
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Research Framework Programme? Not funded by a EU programme Reference Number BAP-2025-731 Is the Job related to staff position within a Research Infrastructure? No Offer Description Build the (mobile) robots
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correlated with plant traits such as yield and stress resilience Collaborate with sensor teams, plant scientists, and data engineers to develop robust, reproducible data workflows Contribute to the development