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performance, and data and product quality. You will join the section in charge of sensor performance, data quality, algorithm development, and calibration and validation (Cal/Val) for the ESA EO missions
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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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of the internship: Machine Learning for recognition of planetary materials from multispectral datasets You are sought to contribute to the ongoing development of Machine Learning algorithms for recognition
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, Directorate of Technology, Engineering and Quality. The Microelectronics Section provides functional support to ESA projects and carries out technological research and development (R&D) in the field
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scientific standards, while offering subject matter expertise to guide ML-based algorithms development. Key responsibilities include expanding, curating and quality-assessing multi-spectral archives within
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knowledge of system security engineering, crypto algorithms and certification processes. Good knowledge of technology development and maturation processes relevant to PRS, security and crypto devices
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as a pathfinder for novel technologies and working methods across all space domains. The overarching goal of this research fellowship is to develop and study advanced theoretical frameworks for deep
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, development and implementation of digital signal processing algorithms and data processing strategies for microwave radiometers; conducting laboratory activities to validate architectural concepts, operating
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acts as a pathfinder for novel technologies and working methods across all space domains. The overarching goal of the research line is to develop and study advanced mathematical approaches, apply them
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climate science to help develop the next generation of EO products and jointly address some of the major science challenges of this decade. The Hub will also contribute to the development of a solid