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-purpose deep learning frameworks, such as Tensorflow or PyTorch; the interest and ability to share knowledge with other ESA organisational units. The following elements are considered an asset: Knowledge
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landscapes. The research will cover the following tasks: Critical review of current compliance levels in ESA projects: data analysis of the outcomes of project reviews conducted since the introduction
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radiation simulation toolkits such as Geant4 and its application, GRAS (Geant4 Radiation Analysis for Space). ESA is a signatory member of the international Geant4 Collaboration together with CERN and a
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theoretical advances into practical insight and tools that can support analysis, design and decision-making for AI-enabled space systems, thereby bridging the emerging scientific theory of deep learning with