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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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state estimation and multi-target tracking algorithms (e.g., Kalman/particle filters, Gaussian mixture filters, random finite set methods, MCMC-based approaches) for SSA/SDA and aerospace applications
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will use the TOPAZ system, the neXtSIM sea ice model, the Ensemble Kalman Filter and remote sensing data. The TOPAZ system and the neXtSIM model are two forecasting systems developed at NERSC
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, ensemble Kalman filters, and physics-informed neural networks (PINNs) enforce conservation laws while fitting observations. The key is to apply the vast amount of physical insights developed in turbulence
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of large data sets. Determining fundamental and technical limits of a measurement, using principles such as the Cramer Rao bound and Fisher information, Gaussian process, Kalman filter, and state estimation