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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain
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Renault et al., 2019) in order to disentangle the different processes involved and to highlight the most important ones ; Perform a future simulation based on basin-scale future simulations developped
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Are you interested in working on a unique geological dataset to understand the evolution of one of the most enigmatic volcanoes? Salary range £44,247 rising to £50,379 per annum Business Unit School of Natural Sciences Closing date for applicants 30-Apr-2026 Are you interested in working on a...
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simulation science-based theories and concepts in social and clinical education. Interests in extended reality (virtual reality, augmented reality, mixed reality) are highly valued for this position
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on virtual humans and advancing simulation science-based theories and concepts in social and clinical education. Interests in extended reality (virtual reality, augmented reality, mixed reality), wearable
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electric order parameters in multiferroic tunnel junctions (MFTJs) can unlock novel non-volatile, low-energy switching mechanisms. These emerging devices offer promising pathways toward next-generation
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radio access and/or core network standards, implement the features in MATLAB and/or OpenAirInterface software for computer simulations, and conduct theoretical research to submit proposals to the ongoing
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 7 days ago
. Implementing existing machine learning approaches for reduced-order modeling, closure modeling, and flow prediction. Proposing new machine learning methods for turbulence modeling and control. Training and