Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
postdoctoral position, in collaboration with Demcon, focusing on off-road SLAM using lidar, camera, and IMU. Do you have a deep understanding of semantic segmentation, SLAM, sensor fusion (lidar, camera, IMU
-
, including multispectral and thermal imagery as well as LiDAR measurements, into ensemble agroecosystem model simulations. The successful candidate will play a key role in developing robust landscape-scale
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
of photonic chips and integrating chips into larger instruments. Applications include remote sensors like microwave photonics radiometers, compact lidar systems. We are interested in miniaturization of existing
-
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
-
project subcontracted through UGA. This project requires high-end skills in Geospatial Engineering & Technology including GeoAI, Geospatial Model Building, Remote Sensing (Satellite, LiDAR) Data Analyses
-
-visitors-with-wildlife-natural-habitats.html Schindling, J., Gibbes, C. (2014) LiDAR as a tool for archaeological research: a case study. Archaeol Anthropol Sci 6, 411–423 https://doi.org/10.1007/s12520-014
-
Location Lexington, KY Grade Level 45 Salary Range $47,278-78,000/year Type of Position Staff Position Time Status Full-Time Required Education MS Click here for more information about equivalencies: https
-
of developing, indicators to track CO₂ emission trends. Activities Process, calibrate, and validate datasets, including Lidar aerosol data, in collaboration with the Atmospheric Optics Laboratory of Lille
-
mission: concept, scientific objectives and data products. Bull. Amer. Meteor. Soc., BAMS-D-23-0309.1, https://doi.org/10.1175/BAMS-D-23-0309.1, in press. The HAWC Science Development Team (SDT) is jointly
-
heterogeneous geospatial data such as LiDAR point clouds, aerial orthophotos, street‑level imagery, and map/cadastral information. A central requirement is topological correctness—watertight, manifold meshes