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Field
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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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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-driven model for assessing the reliability of official network maps (KLIC deliveries). You will build a prototype algorithm that can be used by infrastructure and civil engineering professionals to better
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control and energy-management algorithms for efficient and reliable long-duration operation. Implement hardware-in-the-loop (HIL) and real-time co-simulation for validation under realistic grid scenarios
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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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system-level grid-connected LDES models for grid support Research, design and development of control algorithms for optimal operation of grid-integrated LDES; Develop a co-simulation framework to analyse
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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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in algorithmic design; Possess good communication skills and an excellent command of English. Additional Information Benefits We encourage high responsibility and independence while collaborating with
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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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Are you passionate about developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative