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to navigation and guidance, for example in nominal/degraded/failure modes; ever more complex mission architectures, including constellations, landers, hybrid crewed/robotic missions and cooperative missions with
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trustworthy AI for science. At Eindhoven University of Technology (TU/e), you will contribute to the project’s core technical components: scientific data orchestration and knowledge graphs architecture and
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hyperspectral — to support early warning, strategic situational awareness and the monitoring of emerging risks. A key focus of the fellowship will be the development of explainable AI architectures capable not
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? Which disruptive technologies or paradigms (specific architectures, lightweight adaptation methods, xAI, interpretable-physic awareness, uncertainty quantification, etc.) will you explore? Why is this