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. Responsibilities* Design, implement, and evaluate wireless-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors
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-of-the-art algorithms for detecting and classifying safe landing zones using computer vision techniques in order to design and develop custom models for detecting landing zones in real-time based on drone
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leading experts working at the intersection of technology, policy, and research. Since its launch, KGI has produced influential research-backed analyses of platform governance, algorithmic design
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours 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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Livingston Observatory, Caltech, and MIT. As LHO Scientist, you will have the opportunity to apply your skills to the design, development, implementation, and commissioning of technologies that increase
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software Analyze software for new, moderately complex systems and algorithms Perform data analysis, test and debug software Develop, implement and execute plans and tests Design and apply basic data sources
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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics
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minimize coupling of environmental disturbances into detector systems. Develop techniques and algorithms to characterize and remove noise sources. Study noise couplings, high-power operations, and thermal
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, transcriptomic, and proteomic datasets using open‑source bioinformatics software. The successful candidate will apply bioinformatics algorithms and statistical methods to interpret, analyze, and visualize large
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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