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network. He or she will have full access to the various technical resources required to carry out the project. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8520-FRELEF-201/Default.aspx
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well as systems/neural network processes underlying motor control in animals and humans, in both health and neuropsychiatric diseases. This includes: The successful candidate will be part of the Project INF
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new theoretical approaches for understanding stability, generalization, and feature learning in large-scale neural networks. Further details and application instructions are available at: https
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academic degrees in Computer Science and will contribute to the different project networks within IntCDC: https://www.intcdc.uni-stuttgart.de/research/ . The successful candidate will bridge Computer Science
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-tracking, neuroimaging, non-invasive electrophysiology and computational modelling. We are particularly interested in formal, computational, biologically inspired, generative or neural-network models
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manipulation experiments, development of diagnosis frameworks (e.g., knowledge-guided machine learning, casual inference, and Bayesian neural networks), evaluation of simulation results (e.g., climate extremes
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animal electrophysiology. Familiarity with epilepsy, seizure dynamics, ictogenesis, neuromodulation, or neural network analysis. Experience with small-animal stereotactic surgery, viral-vector
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Institute for Brain Research at MIT, conducts multidisciplinary research on the neural basis of cognition in humans and animal models — spanning the fields of systems, computational, and cognitive
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with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas behind
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unsupervised learning. These methods will be based on new classes of partial differential equations on graphs and new graph neural network models based on diffusion processes. The developed algorithms will be