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. Knowledge of machine learning and deep learning for image and time series analysis; experience with cloud or high performance computing environments is an asset. Ability to communicate results clearly in
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of information on all the minerals found on the Moon, Mars and in meteorites, and the Machine Learning (ML) software that combines deep learning multi-class and multi-label classification algorithms
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of or experience in matters relating to resilience, preparedness and civil-military cooperation in an EU context. Behavioural competencies Education and professional experience A master’s degree in engineering is
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theoretical challenges motivated by astrodynamics, optimisation, control, scientific machine learning, mission design and autonomous systems, translating these into new research directions in deep learning
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combines extended reality development with machine learning techniques to improve interaction, perception, environment understanding, data interpretation, or context-aware assistance in constrained
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close collaboration with other discipline experts, such as software, microelectronics and applications engineers. * except for RF payloads. ** including artificial intelligence and machine learning
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of information on all the minerals found on the Moon, Mars and in meteorites, and the Machine Learning (ML) software that combines deep learning multi-class and multi-label classification algorithms
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, tables, and visual synthesis material to support discussions within the team and contribute to the consolidation of future science strategy documents; apply existing AI/Machine Learning tools to identify
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is to be the “EO innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and
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implementing major industrial procurements. Experience with European Commission projects would be considered a source of added value; Knowledge of computer systems and information/planning/coordination tools