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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design
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methods for their bottlenecks, these steps will then be replaced or supplemented with ML-based surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs
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? Set up a network model to reproduce the main results and provide potential neuronal mechanisms. Existing recordings with optogenetic inactivation could be leveraged to causally verify or reject important
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of American Universities. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/21881217/researcher-x2f-program-officer-membership-network-relations Return
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only
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in complex digital projects - Conocimientos en testing de usabilidad y análisis de métricas UX mediante herramientas especializadas (Maze, Useberry) // Knowledge of usability testing and UX metrics
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, or machine-learning frameworks is an asset Strong analytical skills with a solid understanding of data evaluation, modeling, and interpretation of complex datasets Ability to work independently as
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow