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Location : Remote, US. What you'll do: Utilize data science techniques to analyze and assess the maturity of data taxonomy processes, target systems, and reliant systems. In this role, you will be responsible for leveraging data science techniques to analyze and optimize data taxonomy processes within the Information Systems Security Management (ISSM) environment.
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The PositionThe Science Engagement Division at the Adler Planetarium (Adler) is seeking candidates for a Postdoctoral Fellowship position in the field of Data Science, with an emphasis on Remote Sensing and Geospatial Analysis.
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Experience in Database Administration, Data Warehousing, Data Science, Big Data, Business Intelligence, Artificial Intelligence, Information Systems, Information Technology.
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Job Qualifications: How You Qualify Bachelor of Science (or higher) degree in Meteorology, Computer Science, or a related field, or at least 10 years of relevant experience in computer/systems administration, data operations, and related engineering.
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JOB DESCRIPTION AND POSITION REQUIREMENTS:The Department of Geography at The Pennsylvania State University, University Park, invites applications for a new full-time, non-tenure line faculty position focused on remote sensing and spatial data science at the Assistant Teaching Professor rank to teach and advise students for Penn State's online geospatial education programs.
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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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Familiarity with remote sensing processes, including: processing levels; file formats such as HDF and NetCDF; and data access protocols such as OPeNDAP and WCS; In collaboration with data curators, science subject librarians, and the staff of the Data, Research, Exploration, Access, Methods (DREAM) Lab, the Earth and Environmental Sciences Research Facilitator will create and implement the Library's support plan for researchers in the Earth and Environmental Sciences.
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Land IQ, LLC is seeking a Remote Sensing Scientist in its Sacramento, California office with a specialization in data driven analytics and algorithm development with digital images for agricultural and other land use applications (crop classification, yield modeling, land use impacts, land use change, etc.
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The successful Remote Sensing Scientist candidate will be responsible for working with our growing geospatial team comprised of remote sensing/GIS experts and a range of agronomic, environmental, and other land-based science disciplines.
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BS/MS Remote Sensing/Geography/Data Sciences field (advanced degree preferred) Proficient at remote sensing modeling (e.g., data cleaning, feature selection, analysis, designing, building, and model assessment.
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Remote sensing-based land cover mapping over agricultural areas and crop classification; Applicants must have strong analytical, remote sensing and GIS skills and an exceptionally strong understanding of machine learning algorithms.
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Develop and implement remote sensing and statistical methodologies to perform land use and land cover classification (crop classification) Work in a team environment on a wide range of projects, supporting our team of scientists, remote sensing analysts, and GIS analysts.
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Remote sensing of crop evapotranspiration; and/or. Perform and develop advanced object-based image analysis procedures and methodologies for earth science applications. Resourceful in seeking, preparing, and/or creating raster & vector data.
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Candidate will be responsible for working with our growing geospatial team comprised of remote sensing/GIS experts and a range of agronomic, environmental, and other land-based science disciplines.
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Implement data visualization components and integrate them into the front end, providing users with insights derived from data science algorithms. Our fully remote, international team of 70 (and counting) includes alumni from Google, UBS, Twitter, Plaid, Prudential, LendingTree, Morgan Stanley, Deutsche Bank, and more.
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