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Field
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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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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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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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), 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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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained
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processing (NLP), specific knowledge of machine learning techniques applied to the fields mentioned above (such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), transformers-type
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do they also influence the early recognition of these symptoms by family members and the healthcare team? What links might these factors have with clinical, cognitive, or neural data? Finally, how do
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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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architectures to solve data-driven sensing and control problems related to turbulent atmospheric flows. The work will center around investigation of reinforcement learning and convolutional neural networks