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system, consisting of several components, for processing quantum algorithms, tailored to meet user needs. Developing and testing tooling software, ensuring quality through unit and integration testing
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algorithms developed for the mission. The aim of this project is to develop and test enhanced L2 algorithms for the four hydrological parameters of HydroGNSS, leveraging a combination of machine learning
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website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Algorithmic Optimisation of Stowage for a Cargo Return Vehicle You will help develop a numerical optimisation
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the AI algorithms state of the art for crater detection. generate an overview of available meta data in coordination with the game developers. identify potential use cases in the science community and
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-board Payload Signal and Data Processing algorithms and techniques for RF payloads and instruments in close collaboration with TEC-ED; and Time and frequency references, modelling, design tools
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data, complicated algorithms are required. Some of these algorithms are yet to be developed and/or validated, with real data from polar regions required in order to do so. A dedicated airborne radar
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: designing and developing prototype algorithms for ground processing of Synthetic Aperture Radar images, with a focus on X-band systems; developing Synthetic Aperture Radar image processing; validating and
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to systematically analyse all trench documentation using data-driven methods to better interpret the reliability of underground maps? Your Role As an EngD candidate, you will work under supervision to develop a data
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using AI in Space Exploration You will work with advanced robotic platforms, including humanoids, and support the development of control and interaction concepts in exploration-relevant scenarios. Your
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will: be part of the flight control team of Solar Orbiter. analyze the existing manual workflow and optimize it for automation. develop the algorithm which operates the planning system using the command