104 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" Postdoctoral research jobs in United States
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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Certificates/Credentials/Licenses N/A Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned vehicles No Does
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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, or demonstrate a willingness to acquire relevant expertise rapidly. Proficiency in coding, numerical modeling, and experience with periodic DFT codes or MOLCAS are desirable attributes. The start date
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time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 months ago
). Revisiting Ionosphere-Thermosphere Responses to Solar Wind Driving in Superstorms of November 2003 and 2004. J. Geophys. Res., 122. https://doi.org/10.1002/2017JA024542 . 2. McGranaghan, R. M., A. J. Mannucci
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to launch impactful careers. To learn more about the SCALES Postdoctoral Fellowship Program, visit our program page: https://climate.duke.edu/what-were-doing/scales-postdoctoral-fellows-program/ . Key
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eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https
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/C++, FORTRAN and/or Python. Experience working with geo-spatial information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software
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and to develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST. This calls for expertise across disciplinary sciences – encompassing