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Closing Date Sunday 17 August 2025 Reference PHD002-25 A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media
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be by Prof Sam Wass (www.profsamwass.com ) (UEL, UK), with Prof Davidson (UEL, UK), Prof Rachel Barr (Georgetown, US) and Dr Sarah Jessen (Lübeck, Germany) as co-supervisors. The PhDs will start in
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 11 days ago
program, funded by the German Science Foundation. The PhD position will be supervised by Prof. Werner Becker at MPE Garching. Our offer A versatile, challenging and autonomous job in a dynamic and
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
of Munich (TUM), Campus Heilbronn. We are looking for exceptional candidates who are interested in pursuing a PhD in either theoretical computer science or graph and network visualization. We seek PhD
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of Engineering There is one PhD studentship available in the research group of Prof. Shanwen Tao . Prof Tao’s research activities involve the areas of fuel cells, electrolysers, batteries, super-capacitors
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research the Growing schools; Growing futures initiative, thereby contributing to the research program of the SciTeach Center team, led by Prof. Dr. Christina Siry. The PhD candidate will engage in
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of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicant will be made by Asst. Prof. Eli N. Weinstein. We offer DTU is a leading technical
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Supervisory Team: Prof Middleton, Prof Gandhi PhD Supervisor: Matt Middleton Project description: We know of only 20 or so black holes in our galaxy yet predict there should be 10s of millions
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neutron stars" "Gravitational-wave cosmology: measuring the Universe without a distance ladder" "Building NEMO: The science case for a dedicated high-frequency gravitational-wave observatory" "Searching
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, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control