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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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of a portfolio of data science-based projects which are aimed at assessing the near- and long-term health outcomes for a cohort of Service members who have sustained traumatic extremity injuries. You
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portfolio of data science-based projects which are aimed at assessing the near- and long-term health outcomes for a cohort of Service members who have sustained traumatic extremity injuries. You will gain
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analysis of large, diverse datasets including field experimental data, geospatial data, and time series data. Experience with machine learning and statistical learning. Familiarity with various management
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internal institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences
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, visit the ORISE Research Participation Program at the U.S. Department of Defense . Qualifications The qualified candidate will hold a PhD degree in Biomedical Science, Bioinformatics, Data Science
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. Data management skills and demonstrated experience managing, standardizing, synthesizing, and visualizing large, disparate natural resource (e.g., forest inventory, climate, land use, soils, elevation
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genetic resources, forage legumes, plant genetics, plant breeding, molecular biology, bioinformatics, and data management. Organizational capacity for curating, cataloging, and storing large amounts of data
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. This research will leverage advanced 'omics' technologies and 'big data' analytics to unravel complex pest-natural enemy interactions, understand host associations, and identify adaptation mechanisms at a
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and