317 algorithm-sensor-"University-of-California" Postdoctoral positions in United States
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 5 hours ago
the combination of socioeconomic data and geospatial information. Experience with the calibration and deployment of low-cost sensors is preferred. Occasional travel may be necessary. Field of Science: Earth
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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Software-Defined Networking (SDN) solutions to dynamically manage network congestion and improve communication efficiency. Research and develop topology-aware collective communication algorithms to optimize
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of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills
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project. The project goal is to develop bacterial sensors with the ability to communicate with novel sentinel plants as a readout for changes in environmental conditions or changes in the rhizosphere
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using jets and heavy-flavor probes. The candidate will also participate in algorithm and software development for the LHCb trigger system as part of the Real Time Analysis Project. A Ph.D. in experimental
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Position Description A postdoctoral position studying “algorithms in nature” is available in Dr. Saket Navlakha's research group at the Simon's Center for Quantitative Biology at Cold Spring Harbor
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cloud computing tools and big data workflows A track record of completed research projects Well-written, peer-reviewed papers are expected Interest in using EHR metadata, wearable sensors, and process
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program of independent research with the primary goal of improving the algorithm codes used to characterize the Earth’s gravitational field. Duties will include specialized scientific/numerical analysis
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health and disease, and experience in the algorithms used to analyze these datasets. The appointee will ultimately create an independent research effort with dedicated extramural funding that complements