Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
-
Field
-
, 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
-
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
-
. 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
-
, 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
-
-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
-
-Assembled Terrestrial Ecosystem Simulator) terrestrial ecosystem model and the MIMICS+ module for soil carbon decomposition. FATES simulates and predicts growth, death, and regeneration of plants and