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research project entitled, A community driven modeling approach for identifying community & policy-level interventions to address the impact of structural racism and discrimination on adolescent substance
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology. Description: Wildfires pose increasing risks to ecosystems
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nutrient cycling. This position offers a unique opportunity to investigate how soil microorganisms contribute to soil structure, fertility, and ecosystem functions in both natural and managed ecosystems
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experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and analytical skills in model evaluation Experience in advanced
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. Knowledge and experience of physical testing would be an advantage. The sucessful candidate is resposnible to provide insights into this complex soil-structure interaction problem through numerical modelling
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and ground response (e.g., geotechnical centrifuge testing, lab-scale TBM experiments
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analytical skills in model evaluation Experience in advanced statistical analysis of results Experience with crop model calibration and evaluation, such as DSSAT, APSIM, or equivalent Insight into analyzing
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methodology for analysing long-term spatially structured data sets within a joint species distribution modelling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups
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, the project takes advantage of the unique long-term datasets collected in Finland. REC also develops state-of-the-art methodology for analysing long-term spatially structured data sets within a joint species