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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 2 months ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and
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of complex microfluidic hydrogel networks, integration of micropumps for bubble-free aseptic perfusion, and non-contact mapping of multiple metabolites during tissue culture. You will be working on all aspects
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execute a novel research program at the interface of sensory-motor systems, quantitative behavior, and neural computation. The Audette Lab is a new research group funded by the University of Connecticut and
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: variational formulation of neural network learning convergence of Langevin Monte Carlo algorithms Dissemination of research results through participation in scientific conferences, presentations, and
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associate to support an ethical, legal, and social implications (ELSI) analysis of the NSF funded study “Integrating Human-Derived Neural Networks and AI for Information Processing in Brain Organoids” under
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-university VLIR-IBOF project entitled ‘MINDFUL: MIcroglia directed NeuroDegeneration FUeled by Lipid metabolism’, prof. Dmitriev and prof. Vergult will put their expertise together to establish neural organoid
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for Rokers Vision Lab reporting to Dr. Bas Rokers. 1) Linking Retinal, Neural, and Perceptual Deficits in Visual Disorder: Individuals in the UAE are at substantial risk for perceptual deficits due in part to
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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
, Artificial Intelligence, Neural Networks, Computational Biology, Bioinformatics, Biomedical Informatics or a related field. Programming experience in a language such as Python or R. Experience in writing grant
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and