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physics, atmospheric aerosols, air pollution, remote sensing, or related subjects. Demonstrated experience in the use of active and passive remote sensing techniques, including lidar techniques, ground
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investigating the terrestrial cryosphere and is involved in various high-level research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https
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: https://www.ntu.edu.sg/ase We are seeking a highly motivated Research Fellow to join a research group led by Asst Prof Zeng Yiwen. The successful candidate will work on a multidisciplinary biodiversity
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particular emphasis on integrating satellite LiDAR and UAV data with field observations. Applying statistical modelling, automated machine learning approaches, and artificial intelligence for the analysis and
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cryosphere and is involved in various high-level research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research
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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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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
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and limitations arising from the use of AI-based methods in predictive feedback. The successful candidate will: explore how a combination of multimodal observation (audio, video, LIDAR, thermal vision
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. The successful candidate will: explore how a combination of multimodal observation (audio, video, LIDAR, thermal vision) and physiological measurements (motion tracking, eye tracking, EMG, BCI, EDA, HRV) can be