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. Description: NASA Inexpensive Network Sensor Technology for Exploring Pollution (INSTEP) is a low-cost air quality sensor network utilized in combination with NASA remote sensing datasets to analyze air quality
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, including the Far-Infrared Probe concept, PRIMA. We particularly encourage applicants with interests in processing and analysis of large data sets, development of scientific software, data pipelines, applied
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configurations. The software can assimilate large datasets and perform adjoint computations, inverse modeling, and uncertainty quantification. It has enabled breakthrough scientific discoveries and supported
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. Additionally, we intend to measure root water uptake using sap flow meters. The data will be integrated using recently developed physics-informed neural networks in order to translate apparent resistivity data
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personal professional network with federal, university, and industry scientists through collaboration and stakeholder engagement. Mentor(s): The mentor for this opportunity is Nicholas LeBlanc
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gallium nitride MEMS technology. In this specific project the postdoc will help with developing a thermal infrared imaging micro-instruments working at 500C using GaN based acoustic and micromechanical
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use of software such as R, Python, or similar analytical tools, are helpful. Exposure to modeling water or nutrient dynamics, studying low-water-requirement or salt-tolerant crops, or evaluating
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statistical software such as R. Experience preparing scientific figures, reports, manuscripts, presentations, or other scholarly products. Demonstrated ability to communicate scientific findings effectively