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, and postdoctoral researchers) working at the interface of biology and chemistry. With more than 160 publications since 2001, the team is internationally recognized for its contribution to elucidating
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University, is recognized for its expertise in artificial intelligence and formal methods In this stimulating academic context, we will focus on the problem of explainability of artificial intelligence models
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silicon waveguides with a nanometric core. This work will include the development and optimization of simulation tools for the design of these waveguides, combining numerical results with simplified models
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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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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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offering a postdoctoral position in multi-messenger astrophysics related to the KM3NeT, SVOM, and COLIBRI detectors. The main objective is to complete the development and optimization of the KM3NeT neutrino
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which currently consists of 5 permanent researchers, 2 PhD students, 2 postdoctoral researchers. The PhD studies will be performed in the experimental rooms of the propulsion team at LPP in Palaiseau
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is to provide the most **informative** samples (not just the most probable) to facilitate identification and enhance user experience. - **Theoretical Model Improvement:** Understanding a sample's
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researchers addressing complementary topics and methodology such as Thermodynamic modelling of multi-component planetary degassing/ingassing, Molecular Dynamic simulations of silicate melts, Petrology
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project based on a living model. Consequently, working hours will be adapted to the biological requirements and developmental stages of the model organism. The scientific environment at the Institute