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to teach robots to understand forest well enough to navigate and move through them in real time, using machine learning on LiDAR point clouds and camera imagery for real-time understanding of the forest
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SINTEF. The project aims to develop an automated high-throughput platform for physiologically relevant cell research by combining robotics, microfluidics, advanced sensors, cloud-connected software, and
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relevant cell research by combining robotics, microfluidics, advanced sensors, cloud-connected software, and artificial intelligence. The successful candidate will become part of a multidisciplinary
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/software-engineering/), which has a strong track record in model-based software development and undertakes research on applications in areas such as healthcare, cloud technology and internet-of-things
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or connectivity analysis; machine-learning or deep-learning methods for geospatial analyses; ecological or remote-sensing fieldwork, particularly in alpine environments; Google Earth Engine, geodatabases or cloud
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underlying digital dependencies unaddressed. Even with clear legal frameworks, the dependencies that Norwegian organizations develop on global platform companies, cloud providers, and proprietary software
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System Model, vesion 3 (NorESM3), and a central satellite dataset for EEI is from the Clouds and the Earth’s Radiant Energy System (CERES). The specific tasks intended for the PhD fellow are to (i) Analyze
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as part of the project “UNDER THE CLOUD – Knowledge, democracy, and community rights in Norway’s data centre landscape,” while achieving your doctorate degree. In this manner, you will gain valuable
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networks and/or edge-cloud continuum Document knowledge about the system performance evaluation of computer systems and networks for interactive applications, preferably with AR/VR/XR, robotics, haptics
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rocket or space experiments cosmochemistry. Background on the physics of cosmic dust, meteor studies, ionospheric studies, in situ measurements, meteorite studies, cloud physics, microscopy, advanced image