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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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Job description Offshore wind energy is expanding rapidly, with larger turbines, higher power densities, reduced spacing between wind farms, and deployment in deeper waters. These developments
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Conduct advanced research into atmospheric chemistry and air quality by deploying innovative measurement techniques for the atmosphere, including low-cost air quality sensors and miniature
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systems as well as in flow control technologies. The group’s research is conducted within collaborations performed with European partners such as the European Space Agency (ESA), the German-Dutch Wind
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collaborations performed with European partners such as the European Space Agency (ESA), the German-Dutch Wind-Tunnels (DNW), LaVision GmbH, a Formula 1 team and several other aerodynamics institutes. Since 2000
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; plasmas encountered in planetary magnetospheres; the solar wind and artificially generated charges and fields on spacecraft; micro-meteoroids and non trackable debris; planetary and lunar dust; and
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converter topologies and control strategies delivering DC, high-frequency AC, and hybrid DC-with-AC-ripple outputs to drive resistive, inductive, and hybrid impedance heating, maximizing conversion efficiency
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systems. Job description Would you like to contribute to research on the foundations that support offshore wind infrastructure throughout their full life cycle? We are looking for a motivated Junior
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though optimal sizing of chargers and mobile battery storage systems based on the demand and through energy management strategies under traction and AC grid constraints. Contribute to two pilots
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management strategies under traction and AC grid constraints. Contribute to two pilots that demonstrate and validate: a) a Traction-to-Building microgrid integrating PV, second-life batteries, regenerative