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jurisdictional differences. In carrying out your work, you will gain: a multidisciplinary, systems-level perspective on tackling the space debris challenge; hands-on experience using ESA’s tools and data resources
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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
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novel calibration algorithms, products and tools to maximise the impact of the Biomass mission, in particular during the commissioning phase and the early exploitation phase; studying novel approaches and
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aerospace and space systems while remaining computationally tractable. A key objective is to transform theoretical advances into practical tools that can support analysis, design and decision-making in a
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technology implementations (e.g. ML models) and of high-level products; contributing to the development and curation of open data sets and tools enabling the community to develop its own AI for applications
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conferences, and share tools and data through modern communication channels, including seminars, open-source repositories, and outreach inside and outside ESA; initiate and contribute to interdisciplinary
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biomimetics projects of the ACT, revisiting earlier ideas with new tools, data and perspectives. As an ACT researcher, you will: publish results in high-impact, peer-reviewed journals and conferences, and use