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their influence on climate. The team also has extensive expertise in the development of numerical and statistical models. The Inria AIRSEA project team at LJK develops mathematical and numerical methods
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
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to accelerate formulation discovery. Experimental data will be organised into a comprehensive database and analysed using statistical learning and Bayesian optimisation, establishing a closed-loop framework
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of biophysics, non-equilibrium statistical physics, and cancer biology. Its objective is to understand how stochastic fluctuations and cell-cell interactions combine to drive the spontaneous emergence
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. The developments will also aim to extend existing approaches, which are often restricted to integrated quantities, to the reconstruction of complete statistical fields. The ultimate goal is to design a goal-oriented
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observables, including: the spatial distribution and migration of seismicity, magnitude-frequency statistics and temporal clustering, source properties (strain drop, duration, moment-duration scaling), and
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processing and statistical analysis. The PhD thesis will be supervised by two supervisors, Corentin Louis (Chargé de Recherche CNRS, Observatoire de Paris) and Baptiste Cecconi (Astronome, Observatoire de
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of ideas and behaviors in the Upper Paleolithic. Statistical Network Analysis for the Techno-Stylistic Study of Paleolithic Portable Art During the Magdalenian period (21–14,000 BP), human communities
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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
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demonstrate good organisational and interpersonal skills. The ability and willingness to communicate with the public is an advantage. This project also requires good skills in data processing and statistical