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Field
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. -Experience in one or more of the following areas: wildland fuels mapping, wildfire response field support, land use/land cover change detection, LiDAR. -Proven experience with Python and/or R. -Working
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to capture, synchronize, and label RF, LiDAR, and camera data. - Develop data processing pipelines to evaluate and compare dataset formats for AI/ML applications. - Co-author a NIST Technical
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: https://www.ntu.edu.sg/ase We are seeking a highly motivated Research Assistant/Associate to join a research group led by Asst Prof Zeng Yiwen. The successful candidate will work on a multidisciplinary
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of easterly winds (calima) at Madeira, using observations from the network data from automatic meteorological stations and radiosonde data; Study and technical exploration of a LIDAR system and its use in dust
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, lidars, etc. Experience developing and deploying robotics platforms Proficiency in CI/CD tools like GitHub, etc. Experience with machine learning tools like PyTorch, Yolo, etc. Experience with Robotics
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sample sizes are small. Remote sensing technologies (LiDAR, satellite imagery) can detect and map disturbed areas with high precision, but they do not directly measure essential forest attributes such as
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the SPIN Doctoral School (ed-spin.doctorat-bretagne.fr). This thesis is part of the ANR Ant'noid project (https://anr.fr/Projet-ANR-24-CE33-0218 ). Additional Information Applications must be submitted via
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measurement units (IMUs), cameras, and LiDAR to improve localization accuracy, reliability, and real-time navigation performance in dynamic industrial environments. The project will focus on the design of AI
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for Long-Range LiDAR Systems: in this project, the fellowship holder will contribute to the reconfiguration and upgrade of a femtosecond regenerative amplifier cavity, including the replacement of Pockels
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position). Preferred Education None. Licenses/Certifications None. Required Experience None. Preferred Experience Conducted research in Earth or Planetary Sciences, with experience in LiDAR-based change