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test sites, along with engaging in activities and research in several areas, including: Researching issues and conducting feasibility studies pertaining to the engineering and scientific elements
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on developing knowledge and skills associated with environmental chemical analysis, laboratory- based toxicity testing, and mesocosm/field level assessments. The contaminants of interest include chemicals
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to open-source projects on model reduction, finite element methods, data assimilation and inverse modeling. You will collaborate with researchers by exchanging ideas and technical knowledge in computational
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. Alongside the mentor and the rest of the coastal wetland lab team, the participant will be involved in the collection, analysis, and data entry of biological, physical, and chemical samples from Atlantic
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laboratory studies including toxin analysis, microscopy, molecular methods development and validation, and data analytics. This opportunity will also include engagement with, and training of, stakeholders in
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climate. Observational work would include data from GRACE, SMAP, GPM or in-situ stations. Model diagnosis and analysis can include CLM, VIC, CLSM, and LIS frameworks including GLDAS and NLDAS. Model
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are not limited to: Learning pre-analytical, analytical, and post-analytical aspects of interpreting complex human biological material for specialized molecular genetic analysis. Gaining experience in all
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science. Practical experience in Python programming and database management. Exposure to cloud computing environments and API integration. Development of skills in machine learning and data analysis
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for achieving resiliency. This fellow will also engage on our project to develop and outreach tools for the Tribal Soil Climate and Analysis Network (TSCAN)”. In 2017, the USDA Northeast Climate Hub worked with
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? You will have the opportunity to participate in collaboration with a Principal Investigator (PI) and the project lead responsible for designing experiments and performing data collection and analysis