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) and cover a wide range of innovative topics, from the development and validation of novel methods, algorithms and EO products to innovative climate research; the development of improved climate data
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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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software verification and validation methods and processes, modern software architectures and frameworks, new generation processors and multicores and model-based engineering. The Section also participates
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also assist in evaluating the most suitable spectral identification methods for planetary materials using custom classification software based on Machine Learning techniques. Key tasks include collecting
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/software implementations. Your tasks and responsibilities will include: coordinating with ESA programmes, directorates and external initiatives to align and support industrialisation; facilitating
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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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reduction initiatives, such as a transition to low-carbon energy supply, decarbonisation and the effective use of sustainable products and methods that address social impacts and improve returns; proposing
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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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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