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Field
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to systematically analyse all trench documentation using data-driven methods to better interpret the reliability of underground maps? Your Role As an EngD candidate, you will work under supervision to develop a data
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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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mission products during the exploitation phase, and phase F, including product and processing scenario definition, algorithm definition and evolution for Level 1 and Level 2 products, the calibration and
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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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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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/transformative innovation to help develop innovative EO solutions. We offer: a stimulating multinational, interdisciplinary and open work environment; access to high-performance computing infrastructure and
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of both science and societal application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. With our
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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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-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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through genome sequencing, but these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph