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PHD DEVELOPMENT AND EXPERIMENTAL VALIDATION OF UNDERGROUND SAND-BASED THERMAL ENERGY STORAGE SYSTEMS
28 Nov 2025 Job Information Organisation/Company Academic Europe Research Field Engineering » Thermal engineering Engineering » Mechanical engineering Engineering » Electrical engineering Physics
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towards the end of the project. This will include process intensification and potentially external production runs with industrial partners, supported by experts within the working group. Where to apply E
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25 Oct 2025 Job Information Organisation/Company University of Innsbruck Department Faculty of Mathematics, Computer Science and Physics Research Field Physics Researcher Profile First Stage
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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate 51 Faculty of Physics Startdate: 01.11.2025 | Working hours: 30 | Collective
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on the art world as an interlocked digital and physical system as an ethnographic site. The project uses innovative multimodal methodologies to generate analytical and theoretical advancements on the future as
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate 51 Faculty of Physics Job vacancy starting: 01.11.2025 | Working hours: 30,00 | Classification CBA: §48
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on the art world as an interlocked digital and physical system as an ethnographic site. The project uses innovative multimodal methodologies to generate analytical and theoretical advancements on the future as
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in granular mechanics.PhD position 3# is supported by an Einzelprojekte of the Austrian Science Fund (FWF). The ideal candidate will focus on multiscale modelling of scaly clay failure process in large
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must not have resided in Austria or carried out their main activity (work or study) there for more than 12 months in the 36 months immediately prior to the recruitment date. Selection process Selection
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Control of Skin PigmentationMedical Physics• Neurochemical Characterisation of Epileptogenic and Cognitive Networks with 7T MRSI• Deep Learning for Real-Time B0-Field Stabilisation at 7T MR Scanner• Deep