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infection in mouse models and during virus transmission between the mosquito and the mammalian host. The ultimate goal is to identify host genes and mechanisms that drive variations in host-vector
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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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. Tasks 1. Modeling and analysis of uncertainties The first phase of the research will focus on identifying, structuring, and integrating major sources of long-term uncertainty that influence strategic
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to specialize the memory management of several applications, including virtual machines. Running memory management policies in user space opens up new opportunities, particularly the integration of AI models
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influence parameters used in seismic modeling according to the Eurocodes. DYNATERRE adopts a multi-scale approach—from raw materials to the global behavior of the building. It is based on collaboration
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-analysis and modelling are particularly encouraged to apply. Where to apply E-mail marcello.solinas@univ-poitiers.fr Requirements Research FieldNeurosciencesEducation LevelPhD or equivalent Research
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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Infrastructure? No Offer Description The postdoctoral researcher will contribute to the ANR-funded Pi-CANTHERM project, which aims to design, model, and predict the performance of new n‑type organic thermoelectric
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dozen input variables). The foreseen approach would be to build on recent developments in using CNNs for Species Distribution Models (e.g. Deneu et al 2021, Morand et al 2024) to summarise the complex
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and process behavioral and electrophysiological data • Model behavior based on diffusion models and make explicit link with neurophysiological data • Conduct detailled statistical analysis • Write