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Mellon University is looking for a talented postdoctoral associate to interrogate the circuit dynamics underlying motivated behavior. We are looking to explore the electrophysiological properties of neural
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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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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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is an interdisciplinary effort at the frontier between Biology (Genetics, Genomics), Bioinformatics, Artificial Intelligence (Neural Networks) and Statistics (LMMs). The aim is to join the
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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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to electrophysiology experiments: neural stimulation and recording. A well-established international collaboration network in biomedical research. Support of team members with diverse scientific background. Requirements
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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 9 days ago
/logical rules with neural networks to increase accuracy and explainability. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09730 Requirements Skills/Qualifications PhD in neuro
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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE) enables computations to be performed directly on encrypted data