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Field
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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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service (PaaS) may boost resource efficiency but concentrate value in platforms. This demands comprehensive modelling. Global CGE models based on an IO core with environmental and social extensions. Your
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Job related to staff position within a Research Infrastructure? No Offer Description Position Description: We are seeking a postdoctoral researcher specializing in urban modeling and cost analysis
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 9 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
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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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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 9 hours ago
structures and as there are strong occlusions. The 3D reconstruction of flowers has received relatively little study. An early model reconstructs static flowers using botanical priors [1] by building a shape
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(UM6P) is seeking applications for a Postdoctoral researcher in the field of computational biotechnology and modelling/simulation of bioreactor under aerobic and/or anaerobic treatment of biomass
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Ridge National Laboratory (ORNL) seeks a motivated Postdoctoral Research Associate. This position primarily focuses on large-scale molecular dynamics (MD) simulations and AI-integrated multiscale modeling
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random generation orders during training (a form of structural dropout that preserves information), the model is encouraged to be invariant to the order of variables, which promotes diversity in the search