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sensors. You will be expected to develop and solve algorithms associated with map matching and Kalman filtering, as well as system noise modelling. You will likely have a background that includes strong
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industry partners, Phasor Innovation, on the topic of magnetic navigation with quantum diamond sensors. You will be expected to develop and solve algorithms associated with map matching and Kalman filtering
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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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, Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches NeRF Good interpersonal and communication skills with the ability to tailor communication skills when
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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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of tropical cyclone evolution using the Penn State University ensemble Kalman filter (PSU WRF-EnKF) system with data assimilated from satellite radiance observations. Responsibilities will include producing WRF
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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