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can be found at the URL https://math.univ-cotedazur.fr/~ingremeau/PostdocNuHeMiBa.pdf We are looking for a candidate with a PhD in applied mathematics, with a strong focus on numerical analysis
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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ingredients for Earth-like magnetic fields on millennial time scales in dynamo models. The research activities are two-fold. First, the candidate will run numerical dynamo simulations with various combinations
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and physics, Materials Mechanics, Geotechnics, and Civil Engineering Proven skills in laboratory and/or field experimentation Potential aptitude in numerical modeling Ability to work in a team and in
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between research institutes and industry partners, combining experimental and numerical expertise. This position is part of the ANR DYNATERRE project, which focuses on the static and dynamic behavior
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developments and numerical calculations, especially for objects containing hundreds or thousands of particles. In those cases, it may be convenient to separate the system into several subsystems, some of which
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 11 hours ago
. Familiarity with numerical or symbolic computation tools. Specific Requirements We are looking for motivated and creative candidates who are confortable working both independently and in a team
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. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs … How to apply Applications
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obtained from ex vivo robotic tests will inform multiscale numerical models of tissue mechanotransduction, calibrated using in vivo murine gait analysis and behavioral tracking provided by IRMB
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The successful candidate will be responsible for: 1. Develop the numerical and analytical tools required to design these tunable random architectures and predict the mechanical behavior