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. Validate and test these solutions with respect to the classical methods. choose an appropriate data processing board, optimise the existing software that has been developed, tested, and validated, and then
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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discipline will include: becoming familiar with PA/QA practices, methodologies and disciplines (PA/QA, RAMS (reliability, availability, maintainability and safety), software PA, EEE components, and materials
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learning for dynamical systems, system identification and control systems. This can involve co-tutoring of PhD students or early R&D cooperative studies. contributing to the development of advanced benchmark
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close to completion of a PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD. In particular
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working methods. It interacts externally almost exclusively with academia and operates as a truly interdisciplinary team bound to high scientific standards. Through its research, the team acts as a
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systems, design concepts, lean development approaches, for example Agile, and working methods. Through its daily work, the Team acts as a pathfinder for the low-cost, green launch systems of the future
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, spacecraft system and mission design, and analysis, as well as a valuable data source for studies and other research domains. This research aims to develop a lightweight software system, written in Python and
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close to completion of a PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD. In particular
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aerospace industry, operating in a truly multidisciplinary fashion and fostering research on innovative systems, design concepts, lean development approaches (e.g. AGILE), and working methods. Through its