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automatisk etter tidens utløp. Nedenfor kan du kan se en komplett liste over cookies. Slik avviser eller sletter du cookies Du kan til enhver tid avvis cookies på datamaskinen, nettbrettet eller telefonen din
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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recognised track records. CNAP participates in numerous international initiatives and maintains an extensive global network, making it an ideal environment to build your own collaborative connections. CNAP is
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), latch-ups, and the total ionising dose on spiking neural network performance. develop and test fault mitigation strategies, such as spike-based redundancy, reconfigurable neural routing, noise-aware
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research questions. This postdoctoral scholarship offers the opportunity to be a part of this AI revolution by developing novel neural network architectures specifically optimized for plant genomic data. Our
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preferred: the development of computational models to represent structural performance using commercial and research software tools the development and validation of neural network models focused
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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project funded by the Waterloo Foundation , exploring the neural mechanisms of balance control in children with and without Developmental Coordination Disorder (DCD). This is a hands-on role that will
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project funded by the Waterloo Foundation , exploring the neural mechanisms of balance control in children with and without Developmental Coordination Disorder (DCD). This is a hands-on role that will
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developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and neural networks. The key challenge? Designing robust and stable numerical schemes that remain