12 machine-learning-"https:" "https:" "https:" positions at European Space Agency in Netherlands
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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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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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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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the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: XR and Machine Learning for Onboard Meta Quest 3 Applications on the International Space Station You will
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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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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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intelligence and machine learning frameworks Experience of big data frameworks (data warehouse and data lake technologies) Knowledge of several Al techniques and technologies, such as supervised, unsupervised
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methodologies, such as additive manufacturing, for projects within the centre and for space exploration; developing new ideas around medical technologies, for example, using machine learning techniques to support