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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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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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writing Preferred: Experience with MATLAB (especially for auditory modeling or signal processing) Familiarity with audiological data and test batteries Working knowledge of French is a plus Candidates
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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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guidance. Responsibilities The recruited postdoc will be responsible for: Taking initiative in selecting appropriate AI models for memory access prediction. Driving the experimentation and evaluation process
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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
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3 Sep 2025 Job Information Organisation/Company Nantes Université Department LS2N Research Field Computer science » 3 D modelling Researcher Profile Recognised Researcher (R2) Positions Postdoc
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/Qualifications The recruited candidate should have proven experience in experimental work (setup, data processing, and analysis of results). Skills in nonlinear numerical modeling are also desired. Specific
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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