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rates. This PhD project focuses on developing a mathematical model to predict and analyze the effects of using a gene-drive strategy to control Schistosoma mansoni directly, rather than through its snail
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science Mathematics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 7 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1
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, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
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and guide policy insights; ● Publishing methodological and applied findings, and presenting at international conferences. Your PhD will thus lie at the interface: you'll not only build mathematical
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. Activities: Development of mathematical models. Development of probabilistic inference algorithms. Code implementation, with a particular focus in Julia. Method validation. Application of models on curated
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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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Targeted Project Complexflows, which aims to promote and structure the interactions of mathematics with other sciences around current issues. The thesis will be co-directed by F. Radjaï (LMGC, ED I2S 166
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). Knowledge : PhD in ecological modelling, statistics, mathematics, geographical projections. Fluency in English (written, read and spoken). Transverse skills : Project management, Methodology and analytical
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of numerical ice shelf models has recently been developed to study, among other things, the realistic behaviour of the dynamics of a floe assembly, based on a granular approach. The purpose
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
tools for solving these problems. The goal of this PhD is to understand how these results could be integrated or inspire the designing process of the models for the deployment and the execution of Cloud