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This position is part of the Dutch research project RELEASE (Reversible Large Scale Energy Storage). RELEASE aims to create fundamental scientific insights and to develop, implement and demonstrate
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We are looking for a motivated and independent PhD candidate to develop highly efficient and robust surrogate models of a multi-scale cardiovascular ‘digital twin’ modelling platform. A
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PhD position in obstacle-resolving simulations of urban flows As the impact of global warming on extreme weather events, including droughts, heat waves, unhealthy pollution levels, as well as storms
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Energy Department provides expertise in these areas throughout the entire energy system chain. The department owns a large ESP Laboratory assembling High Voltage testing, DC Grids testing environment, and
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propulsion concepts to support smart green shipping in the upgrade of existing ships and building of new vessels. The PhD research will analyse the basic physics of tacking ships and seek for innovative
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particles to shifts of prevailing cloud regimes in response to changing weather statistics. During your PhD research, you will explore concepts from complex systems theory and data-driven approaches
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without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty
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aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge
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model complexity and function approximation. You will be welcomed into our Sequential Decision-Making group, where we focus on various aspects of reinforcement learning. During your PhD, you will have the
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subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other