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Field
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images to estimate drift and deformation fields to study sea ice dynamics. Extract ensemble drift model information to predict future sea ice locations. Integrating past knowledge and ensemble drift
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, and different snow depth products versus simply using the mean SIT Intercompare seasonal forecasts for the sea ice edge location based on the assimilation of SIT observations into the different ensemble
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Weather an Water Extremes (CW3E; http://cw3e.ucsd.edu/ ) goals in improving ensemble Atmospheric Rivers (ARs) prediction. Qualifications Basic qualifications (required at time of application) The positions
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. Moreover, the successful candidate will also need to develop a system to estimate the uncertainty of the predictions. Potential solutions could include ensemble generation, a combination of EOF
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. FATES simulates and predicts growth, death, and regeneration of plants and subsequent tree size distributions by tracking natural and anthropogenic disturbance and recovery. It does this by allowing
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-time fault prediction. ML models, such as deep learning, reinforcement learning, and ensemble techniques, can analyze large-scale operational datasets from hydroelectric power plants, identifying
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, or ensemble models (e.g., XGboost). Proficiency in programming languages commonly used in data analysis, such as R, Python, or C++ (or similar). Strong communication, collaboration, and presentation skills
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behavioral paradigms in mice. Aim 3: Validate the model and generate testable predictions 3.1. Evaluate key variables within the model to investigate overwrite vs sidelearning in memory unlearning. 3.2. Use
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scientists to join the NOAA Research Global-Nest Initiative. This multi-laboratory project aims to develop ultra-high resolution atmospheric prediction models for better prediction, understanding, and
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MIMICS+ module for soil carbon decomposition. FATES simulates and predicts growth, death, and regeneration of plants and subsequent tree size distributions by tracking natural and anthropogenic disturbance