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and working methods across all space domains. The overarching goal of this research fellowship is to develop and study advanced theoretical frameworks for deep learning, understand their mathematical
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competitiveness. .Our vision is to be the “EO innovation hub”, connecting EO with a growing ecosystem of disruptive and transformative innovation such as AI, ML, quantum computing, edge computing
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professional experience. Additional requirements Knowledge of and interest in multidisciplinary analysis, software engineering, and numerical methods would be considered an asset. Diversity, Equity and
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configurations into account, computing atmospheric entry trajectories and launch windows, propellant budget analysis, predicting orbit-derived data, orbit determination and navigation analysis, planetary
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innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and photonics. Many of the
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. Technical competencies Demonstrated ability to provide technical leadership, strategic guidance and independent judgment in complex programme environments involving multiple parallel activities
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. You will utilise ESA-supported cloud computing platforms for conducting your research. By the end of the traineeship, you will have gained practical experience in scalable Earth observation
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through development and validation, identifying how technology maturity, SatCom system requirements, data and computing needs, validation requirements and operational constraints need to be addressed
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their signature and monitoring. In parallel, the Division contributes to the improvement of the overall regulatory framework in the Contracts Department, while supporting the Department’s general efforts
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achieve organisational goals; operational efficiency, including excellent planning and organisational skills and the ability to manage several tasks efficiently in parallel; openness to change and