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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 17 days ago
(Bordeaux) and half at Airbus (Toulouse). Safer and cheaper aircrafts require new concepts, and increasingly complex geometrical, physical, and numerical modeling. These new models must integrate multi
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, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and manufacturing details. This de-featuring is not
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funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Data integration and numerical modelling
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expected to contribute to other activities and tasks within the ENER-G project. The main outcome(s) of the PhD will be novel optimisation models and solution algorithms that will substantially advance
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health in Europe. This project is part of Work Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN doctoral training network. The recipient of this PhD position will carry out research
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to the space-based LISA observatory. The research will advance post-Newtonian waveform modelling through improved analytical techniques, incorporate strong-field information from numerical relativity simulations
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focuses on the modelling of electrodes for redox flow batteries to clarify the influence of electrode surface properties on the macroscopic electrode properties. Pore-scale electrode modelling and numerical
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methods: The Met Office aims to help its customers stay safe and thrive by producing reliable weather and climate information. Numerical models of the climate system are an important tool to help achieve
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, observation, modelling) in conjunction with major research infrastructures in the field, both on the ground (including the giant ELT telescope) and in space (CNES and ESA programmes). IPAG is a unit of the
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has gone through a very rapid development in the last few years. Large-scale machine learning models are however notoriously over-confident. With insufficient amounts of data to train them on together