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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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collaborate closely with Professor Colin Meyer at Dartmouth College to develop new models of polynya dynamics, efficient algorithms for inversion of surface signatures, and deeper understanding of controls
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-computer interaction. The ideal candidate will have a strong foundation in algorithms, HCI, and software engineering, and will contribute to the design, development, and evaluation of interactive and
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on greenhouse gases, air quality, and emerging satellite missions. Key responsibilities include developing and evaluating remote sensing methodologies, including designing algorithms to detect and quantify marine
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-computer interaction. The ideal candidate will have a strong foundation in algorithms, HCI, and software engineering, and will contribute to the design, development, and evaluation of interactive and
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by working on research projects in AI safety and robotics, contributing across the full research lifecycle: algorithm and system design, code development, experimental validation, and scientific
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple
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pipelines for large-scale scattering datasets. Participate in synchrotron experiments at APS beamlines to generate datasets that support algorithm development and validation. Work closely with ISAAC
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problems in biomedical field, interact with world class scientists, and gain experiences and develop skillsets for their next career stage. The computational biologist is expected to develop new