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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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BIOS-06/A - A synaptic mechanogenetic technology to repair brain connectivity - CUP: J93C22002400006
of neural networks. The technology will be validated in mouse models of neurological disorders. Where to apply Website https://pica.cineca.it/units Requirements Additional Information Eligibility criteria
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learning algorithms for closed-loop optogenetic control of neural circuits (DC2). The appointed DCs will participate in an international research team as part of the EU-funded Marie Skłodowska-Curie Actions
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Dipartimento di Fisiologia e Farmacologia - Sapienza Università di Roma | Italy | about 2 months ago
Electroencephalography (EEG) and magnetic resonance imaging (MRI) can detect early alterations in neural networks that manifest as cognitive and sleep-wake cycle disorders in the early stages of Alzheimer's disease
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The Laboratory on Social & Affective Neuroscience is located in the Department of Psychology at Georgetown University. We conduct research aimed at understanding the social, cognitive, and neural basis
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foundational and advanced Artificial Intelligence topics such as Python programming, data analysis, machine learning, artificial intelligence tools and frameworks, neural networks, and ethical considerations in
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passionate about applying ML algorithms and developing AI applied research and innovation solutions using classic ML to novel transformer neural networks. We test and measure the real customer impact of each
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learning, physics-informed neural networks, graph neural networks, transformers, convolutional defiltering methods, etc.) for the integration in multi-physics simulation codes You will develop code for and
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or more of the following research fields: Quantitative finance Neural Networks Financial Engineering and Risk modelling Wealth management, payment and lending AI/Machine Learning applications in financial
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classification of Aluminium 5083 TIG welding using HDR camera and neural networks. J. Manuf. Process. 45:603–613. https://doi.org/10.1016/j.jmapro.2019.07.020 Wang R, Wang H, He Z, et al (2024) WeldNet: a