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Field
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epilepsies. They use a range of advanced genomic techniques including single-cell and spatial multiomic evaluation of epilepsy surgical tissue as well as iPSC-derived neural cultures and mouse models
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analysing Cortically-Embedded Recurrent Neural Networks (CERNNs) that simulate large-scale neural dynamics during cognitive tasks. These models integrate species-specific neuroanatomical constraints to enable
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to modulate physiology and neural activity in the brain, gastrointestinal (GI) tract, and other peripheral organs. These projects have a high potential for translation towards treating a variety of neurologic
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fundamental questions about the transcriptional regulation of inhibitory neuronal development and function in neural circuits, the role of cerebellar circuit dysfunction, and disrupted gene regulatory networks
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of research include diagrammatic calculations, quantum Monte Carlo methods, density matrix renormalization group and tensor network states, and artificial intelligence and neural networks, with a particular
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), Multilayer Perceptron (MLP), Autoencoders, Convolutional Neural Networks (CNNs), and Kolmogorov–Arnold Networks (KANs). Desirable knowledge of Gradient Boosting models such as HistGBM, LightGBM, and XGBoost
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be found on our lab website: https://www.derosierelab.com/ Salary and benefits: ~€2300 net per month for candidates with less than 2 years post-PhD experience; €2450+ net per month for candidates with
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and conferences related to the topics of the position Expertise in one or more of the following areas: Wireless and satellite communications AI/ML for dynamic networks including Graph Neural Networks
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force fields (MLFFs) that combine state-of-the-art equivariant neural network architectures with robust, well-calibrated uncertainty estimates. These models will enable fully automated active learning in
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and implement Bayesian graph neural networks and convolutional neural networks as surrogates for high-fidelity biomechanical models Quantify and propagate uncertainty, and develop strategies for model