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. Skills in computational modelling or machine learning applied to brain signals are an asset. We are looking for a highly motivated, rigorous and curious researcher who is ready to invest themselves in a
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of GIS, spatial statistics, or other spatially relevant methods. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology
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. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with an emphasis on pattern identification, prediction, or spatial risk mapping
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Computational Neuroscience and off-site experts in The Virtual Brain (in particular, Spase Petkoski at INSERM / Aix Marseille University). Key responsibilities: • Fitting TVB models to the multimodal patient
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
PhD supervisors and co-direction Name: GAUCI Surname: Marc-Olivier Grade: HDR Institution: ICARE, Inserm U1091 Email: gauci.mo@chu-nice.fr Phone number: 04 92 03 70 27 Name: Micicoi Surname