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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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intelligence (AI) and machine learning(ML). Duties This position combines knowledge of the Earth observation (EO) domain (EO instruments, EO data, EO algorithms, modelling, etc.) and AI/ML, as well as data
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(meta-data) remain reliable, traceable, and well-documented, which will be the backbone of our high-quality research. Additionally, you support the team in hands-on practices such as cell and tissue
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collaborate with software engineers, systems engineers, and operations specialists, and you will see your algorithms tested on realistic scenarios and data. Candidates interested are encouraged to visit the ESA
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Location ESRIN, Frascati, Italy Description Data Quality and Cal/Val Manager for Atmospheric Sensor Missions in the Sensor Performance, Products and Algorithms Section, Earth Observation Mission
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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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scheduling to help make offshore wind farms a reality. Job description This post-doctoral position focuses on developing fundamental algorithmic advances for dynamic planning and scheduling in multi-objective
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meta-analyses developed by the team are published in international scientific journals. The BMA team is part of the Microbiology & Agro Chains business unit, which consists of six teams. In
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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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our society leads to massive changes in the energy sector. The future electricity system must be flexible, inclusive, digital, distributed, agile, and renewable, while the levels of reliability, safety