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-time data acquisition and telemetry systems Familiarity with cloud computing platforms and edge deployment of ML models Experience with uncertainty quantification, sensitivity analysis, or robust
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This PostDoc project focusses on extending an existing digital twin platform called DTaaS with better support for collaboration between different legal entities in a secure manner. Digital twins
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | about 2 months ago
investigate together the chemical and physical evolution of the interstellar medium and star- and planet-forming regions, from clouds to disks, with links to exoplanets and our Solar System. The start date is
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navigation, trajectory planning, and point cloud mapping; and (3) deploy the developed algorithms on a physical mobile robot operating in GPS-denied, low-light, and geometrically repetitive environments
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of water vapor: How does vapor buoyancy affect the momentum balance and large-scale circulations in Earth's and other planetary atmospheres? How does vapor buoyancy regulate clouds and Earth's energy balance
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further secured by Quantum Encryption techniques. On the other hand, optical links are affected by clouds (overcome by making various sites on the ground available) and turbulence in the atmosphere
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to PhD level in an area related to Computer Science, the applicant will be proficient in software development, systems administration, networking and cloud. This is an invaluable opportunity to develop
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, maintaining, and documenting open-source software tools or R packages Experience with geospatial analysis, environmental databases, and cloud or high-performance computing workflows Demonstrated record of peer
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 17 days ago
proficiency in scientific programming (Python or R) and deep learning frameworks (PyTorch or TensorFlow) is recommended, alongside experience processing large spatial datasets using cloud or high-performance
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI