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power electronics to enhance the reuse and recycling of components, enabling a more circular life cycle. The work will contribute to a new paradigm in the development of power electronics that incorporate
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loading histories in Francis turbine runners, including start–stop cycles, rapid load changes, dwell periods and mixed high–low stress sequences. Such loading conditions influence fatigue damage development
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Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship – to develop and support implementation strategies that address
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understanding how men could fare better in the modern world. Within the project, the successful candidate will be able to develop a research agenda focusing on health effects of men’s participation in the family
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Recent advances in artificial intelligence (AI) have fuelled the idea of building “AI scientists”, i.e., systems that can perform part or all of the research process on their own. The development
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placement within Siemens Digital Industry Software. Project Overview The project focuses on developing and integrating ML techniques to enhance wall treatments for under-resolved boundary layers in
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simulation, composites manufacturing and advanced sensing techniques. The project will provide opportunities to develop skills in these areas and contribute to the development of the next generation composite
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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studies, sociology, anthropology, community development) or relevant undergraduate degree with honours demonstrated research capacity and critical thinking skills commitment to critical, feminist
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack