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your arrival. The EM2C laboratory is seeking a highly motivated candidate for a PhD in data-driven, physics-informed, and probabilistic modeling of turbulent combustion. The PhD work will combine
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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the anticipation of adverse events. To achieve this, the simulator will need to simulate numerous scenarios based on the current situation and will also rely on forecasting algorithms. The simulator must also enable
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improve the parameterization of rheology integrated into current large-scale sea ice models, particularly those used for real-time forecasting and/or in the context of coupled climate simulations