147 parallel-computing-numerical-methods positions at European Space Agency in Netherlands
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/transformative innovation in the sector. Our vision is to become an “EO innovation hub”, connecting EO with a growing ecosystem of disruptive and transformative innovation, encompassing AI, ML, quantum computing
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develop methods for efficient covariance/uncertainty propagation that are suitable for embedded use on space processors. The goal is to develop methods that can be used to perform real-time covariance
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directly to the upstream swt-initiative31/skija prototype, focusing on: rendering logic. layout behavior. and basic widget implementations. In parallel, they will evaluate how the Skija backend could be
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REFM deliverables across sites by establishing a common set of strategic objectives, guidelines, performance and quality management systems, optimised methods and processes, planning and coordination
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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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Simulation Methods including scientific data processing and databases, software applications including human computer interface, support for science operation centres and downstream applications; Supporting
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the Mechanical Department laboratories and computing infrastructure, including the thermal computing facility, in conjunction with the TEC infrastructure function; Analysis methods and tools for the thermal
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navigation. The task also includes the development of the necessary analytical and numerical methods and software tools. Candidates interested are encouraged to visit the ESA website: http://www.esa.int Field
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detection is set according to the local statistics of the radar sea clutter. The threshold method works well for large ships due to their high intensity value compared to sea clutter. However, in cases
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integrate modern AI methods into control and decision-making, enabling humanoid robots to adapt to unpredictable environments and support astronauts more effectively. The project contributes to ESA’s efforts