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technological research and development (R&D) concerning turnkey onboard hardware data handling solutions, with an emphasis on: platform and payload data handling architectures and their building blocks (equipment
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under dynamic workloads, strict real-time constraints, and limited computational resources remains a key technical challenge. This PhD project addresses these challenges by developing efficient
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and democratic participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal
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, architecture, and development of prototype and product versions of our semiconductor test tools. Translate research algorithms into production-grade, maintainable software. Build and manage a small high
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems
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. This includes modelling, data analysis and algorithmic development, as well as experimental validation of models and algorithms. It contributes to the performance assessment of space missions. More specifically
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emerging big data technologies, to maximise impact and benefits for society. Reporting to the Head of the Applications Section, you will be responsible for defining and managing EO research and development
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Systems Section - and - EO Data Architect and AI Expert in the Ecosystem Development Section within the Copernicus Ground Segment and Data Management Division, Earth Observation Mission Management and
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the definition, design and development of PNT system evolutions, including multilayer systems and related technologies, and covering end-to-end system, architecture, signal, performance, receiver, algorithms and
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remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades. Using upstream