150 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at CNRS in France
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» Modelling toolsEducation LevelPhD or equivalent Skills/Qualifications PhD in physics, applied mathematics, signal and image processing, digital imaging. Specific Requirements The candidate will work in a
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FieldChemistry » Computational chemistryYears of Research ExperienceNone Additional Information Eligibility criteria PhD in chemistry or physics with a focus on modelling Knowledge of molecular simulation
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In this postdoctoral project, we aim to study and model the microstructure of confined foam and the mechanical properties at the pore scale involving a few particles. This work will involve both
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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - a PhD degree in computer science or equivalent - solid knowledge of telecommunication networks - knowledge of modeling and
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a PhD in Computer Science, Applied Physics, Applied Mathematics or other relevant fields, with both good programming skills and good knowledge in numerical algorithms. Website for additional job
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Additional Information Eligibility criteria • PhD in paleoecology, disturbance ecology, or community ecology. • Strong knowledge of dynamic vegetation models (e.g., iLand, LANDIS-II). • Strong skills in
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specific model grid, in a sample of galaxies with direct X-ray observations for calibration and validation. This project will be led by a postdoctoral researcher at AIM, who will also use far-UV observations
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14 (3 postdocs, 2 PhD students, 3 CNRS researchers, 5 engineers, 1 animal technician). The laboratory studies neural stem cells using the zebrafish brain as a model. We aim to understand how cell
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part of the European project ULTRABAT (BATTERY2030+), you will be responsible for modeling the NMR parameters of lithium ions in and at the interface of battery cathode materials. The ULTRABAT project
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intelligence at the Laboratoire de Physique Corpusculaire (LPC) in Caen, France. We're seeking an innova-tive postdoctoral researcher to develop Large Representation Models (LRMs) for the KM3NeT neutrino