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digital twins using prediction-powered inference to enhance reliability assessment; The theoretical analysis and algorithmic development of methods rooted in statistical learning theory, multiple hypothesis
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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This position focuses on the research and development of novel radiation detectors and associated edge-computing circuits and algorithms for X-ray, particle, and nuclear physics experiments
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patterns may mimic those observed in irrigated croplands. Key Responsibilities: Conduct research to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate
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academic research lab environment -Software programming for scientific simulations -Interdisciplinary and multi-physics relevant strong background -Design of computational algorithms for 1st /2nd order time
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to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate methods for detecting the timing and frequency of irrigation events from time-series remote sensing
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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human
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, develop, and implement state-of-the-art post-quantum cryptographic protocols and algorithms. Collaborate closely with top-tier European universities and industrial partners. Participate in project
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL). Northwestern, TTIC, and UIC. Position ID: Northwestern-The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL