Internship: Extended Object Tracking
The Control and Dynamical Systems group at MERL is seeking a highly motivated intern to conduct fundamental research in extended object tracking with possible applications to autonomous driving. Previous experience on extended object tracking algorithms based on any of extended/unscented Kalman Filtering, particle filtering, interacting multiple model (IMM) tracking, probability hypothesis density (PHD) filtering, Random Finite Sets, data association, and jointly data association and prediction/filtering (joint probability data association (JPDA), multi-hypothesis tracking (MHT) is highly preferred. Ph.D. students with research focuses on statistical signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with flexible start date, with possible extension.
Contact: Jay Thornton
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