78 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" positions at European Space Agency
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intelligence (AI) and machine learning(ML). Duties This position combines knowledge of the Earth observation (EO) domain (EO instruments, EO data, EO algorithms, modelling, etc.) and AI/ML, as well as data
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value. Knowledge of computer systems and information/planning/coordination tools (such as esa-p, Microsoft Excel and Microsoft Project) is essential. Familiarity with modern dashboard and risk management
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lessons learned and best practices, to enable learning, ensure consistency, and improve quality across teams and projects) Behavioural competencies Education A master's degree in a relevant domain is
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for space applications; Leading the centre of excellence for advanced simulation methods including scientific data processing and databases, software applications including human-computer interfaces, support
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motivating work environment and promoting good team spirit; supporting team members with ongoing professional development by encouraging learning and delegating responsibilities; identifying, assessing
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management (Ability to capture, organise, and share knowledge, including lessons learned and best practices, to enable learning, ensure consistency, and improve quality across teams and projects) Behavioural
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; streamlining, improving and providing regular training on ground segment processes related to the Navigation Quality Management System; ensuring that the lessons learned for the Galileo ground segment
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relationship management and communication skills; the ability to drive your team’s performance, developing your people by encouraging learning, delegating responsibility and giving regular and constructive
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management and communication skills; ability to drive your team’s performance, developing your people by encouraging learning, delegating responsibility and giving regular and constructive feedback; strong
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methods, including lessons learned and knowledge management, and to the reflection on the evolution of the Division’s role and activities; contributing to the (independent) technical assessment capability