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• Expertise with Kalman filtering (KF), extended KF, or other sequential model-based estimators • Experience with conducting research in navigation applications for robotic or automated transportation
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Julia and/or Matlab and/or C++. In addition to the above, to be successful for Level B you will also need: Experience in state estimation, target tracking, and data fusion algorithms such as Kalman
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estimation, target tracking, and data fusion algorithms such as Kalman filtering, Particle filtering, and Multiple-hypothesis tracking. A strong track record of high quality research as evidenced by
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will join our interdisciplinary research team to develop an Ensemble Kalman Filter (EnKF)-based coupled data assimilation capacity for the DOE’s Energy Exascale Earth System Model (E3SM) and the regional