Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
-
carbonated particles; - transformation of monophasic phases to multiphasic; - hydration execution as a cycle of dissolution, diffusion and precipitation. Secondly, the created numerical model will be
-
Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 1 day 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
-
will be modelled by analytical and numerical approaches. Existing analytical approaches will be used as a tool to describe the behaviour of fire exposed TRC in tension, while numerical simulations will
-
conditions such as pressure or temperature, rocks and metals undergo PTs to achieve thermodynamic equilibrium. In minerals, investigation of mineral assemblages provides essential insights
-
methodology such as Thermodynamic modelling of multi-component planetary degassing/ingassing, Molecular Dynamic simulations of silicate melts, Petrology of melting of exoplanetary mantles, and the partitioning
-
companies will also be studied. The optimization model will encompass the modeling and implementation of several technologies, including steam networks, hybrid power systems, and auxiliary and storage
-
of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
-
. This approach aims to enable the development of computationally efficient models for simulating radiative transfer in three-dimensional cloudy atmospheres. Where to apply Website https://emploi.cnrs.fr/Candidat
-
, extinctions, and environmental change; ● Running simulations and scenario analyses to explore how different discounting rules or time preferences shift optimal conservation choices; ● Fitting models