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Health Readiness System (DOEHRS) experience with analytical instruments and water analysis ability to follow directions strong written and verbal communication skills required. Application Requirements A
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to assist with modeling efforts Develop methods to assess model accuracy, scalability, and utility for use in wildland fire decision making. Model sensitivity analysis and testing on independent data
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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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investigation and developing software algorithms and techniques to support human or machine information interactions for the purpose of information retrieval/dissemination, analysis and/or decision making
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quantitative analysis, with experience in biosignal data collection and/or analysis recommended. Researchers having familiarity with multi-aspect data approaches are encouraged to apply, with programming skill
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research and analysis in the Army. US citizenship is required for this research opportunity. The successful candidate will assist with the development of novel nano-mechanical test methods for and
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research and analysis in the Army. The Composites and Hybrid Materials Branch of the US Army Research Laboratory is looking for an applicant in the area of polymeric materials characterization to carry out
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, topological data analysis, and machine learning to understand data relationships generated by either our simulations or from experimentally acquired neuroimaging data. Applicants should have a strong