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classes and their roles in scientific applications, such as deep neural networks (DNNs), convolutional neural networks (CNNs), transformer models, and graph-based neural networks. Familiarity with software
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groups, you will gain opportunities for international exchange and build a strong global research network that supports your long-term career development. Your mission We are recruiting a Postdoctoral
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, information processing, mathematical models, neural networks, learning theory For additional details, refer to the lab’s webpage. Toyoizumi Lab https://toyoizumilab.riken.jp/ * details of the business RIKEN is
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling
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The postdoctoral researcher will join the "Network Dynamics & Computations" team led by Srdjan Ostojic and develop research projects on modeling neural circuits and their role in behavior. The work will focus
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research, all with the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five
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) methods. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5253-MOUBEN-002/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldChemistryEducation
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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communications Computing & Networking: QuMIMO, Quantum Error Correction, Multi-partite systems, Q Network Coding, HQCNN - Hybrid Quantum-Classical Neural Networks Security & Logic: QRL - Quantum Reinforcement