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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data
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learning with a background in robust and embedded control, aerospace systems and physical modelling, as well as in artificial intelligence-related concepts, computer vision and numerical optimisation
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approaches. You will join a diverse, evolving, and interdisciplinary research team embedded in a large space agency, in contrast to a more specialised, focused research group with similar competences. You are
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; analyses: support of different data analyses including thermal, mechanical or test results to ease the validation of systems and subsystems. Embedded AI, optimisation of models, improvement of performance