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REQUIREMENTS The College of Earth and Mineral Science is seeking applicants for part-time job of: Researcher interested in lithium and REE distributions in igneous and metamorphic rocks. Job duties to include
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atmosphere. Examples of such processes include the cycling of trace gases and water vapor in the Amazon rainforest. Figures need to be created to display spatial and temporal patterns of trace gas distribution
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giving platform (DonorDrive®), Storefront, Power BI data analysis, and creation and distribution of email campaigns. Fundraising program support – assist with specific needs of Mini-THON®, Lion’s Club
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Sriperumbudur. Potential research projects include (but are not limited to) developing theory and methods for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows
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distribution system. Qualifications & Requirements: MS in Mechanical Engineering. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s) in
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electronics. Specifically, they will be setting up laser systems, including laser frequency stabilization setups based on atomic spectroscopy, frequency distribution setups based on acoust-optic modulators, and
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for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine
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position. The student researcher will be asked to assist in computational polymers research. The successful applicants will assist in our work to explore digital representations of polymer aggregates
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of near surface by processing DAS noise data. This will be applied to field data distributed acoustic sensing (DAS) fiber optic data for near-surface characterization. BACKGROUND CHECKS/CLEARANCES
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REQUIREMENTS The Department of Computer Science and Engineering is seeking part-time Research Assistant/Programmer to assist with robotics and machine learning research as well as data collection and data