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developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and neural networks. The key challenge? Designing robust and stable numerical schemes that remain
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on methods such as functional connectivity analysis, brain network analysis, or machine learning; Excellent scientific writing and communication skills in English; Ability to work independently while
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their expertise together to establish neural organoid models recapitulating aspects of neural-microglia interactions in neurodegenerative diseases at Ghent University. About project MINDFUL: Lipid accumulation in
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, implement, and evaluate computational models that assimilate 2-photon data (60%) Use a computer programming language to create novel neural network simulations (models) that include realistic simulations
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-reconstructions and observations, low-order data assimilation, or deep neural networks. A quantification of the impact of mesoscale and submesocale features is also expected. At a later stage, the successful
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solution a serious computational challenge. This project aims to tackle that head-on by developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and neural
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extensive expertise in electrophysiology to join international research team "Astrocyte-Neuron Networks" lead by Prof. Dr. Cristina García Cáceres at the Institute for Diabetes and Obesity (IDO
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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of mammalian brains using mice as an animal model. Three main lines of research include 1) the brain-wide mapping of brain cell types including GABAergic neurons, glia, and cerebrovascular network, 2) anatomical