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Organization U.S. Department of Defense (DOD) Reference Code EACE-2025-0004 How to Apply Click on Apply at the bottom of the opportunity to start your application. Description The Extremity Trauma & Amputation Center of Excellence (EACE) is offering a fellowship at the San Diego, California...
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audiences. We’re looking for someone who: Can apply data science to real-world problems. Is comfortable with Python, R, SQL, or similar tools for analysis and modeling. Can translate messy datasets
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Science, Engineering, Business, Data Science, Data Visualization). • Demonstrated experience in data visualization – dashboards (tableau, R shiny, etc.) • Demonstrated experience in GIS and spatial mapping
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to wrangle, clean, summarize and analyze qualitative and quantitative data using data analysis software, such as excel, R, and NVivo. The fellow will also gain experience in literature reviews, writing results
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: Build reproducible workflows, functions, and R or Python packages; develop visualization tools and open-source applications; and share code through collaborative platforms such as GitHub. Scientific
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is with the Research and Operations (R&O) Directorate within DEVCOM CBC, which has more than 400 employees including over 100 PhD staff members with chemistry, biology, physiology, and engineering
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biology, and mass spectrometry methods to develop capabilities for the detection of and protection from current and emerging biological threats. The fellowship is with the Research and Operations (R&O
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in statistical programming (R, Python, Julia, MATLAB). Familiarity with GIS and spatial analysis tools (ArcGIS, QGIS, or R spatial packages). Ability to integrate multidisciplinary datasets
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Nanopore MinIon platform. Conducting analyses using the most state-of-the-art software and bioinformatics tools. Programming experience using Linux, Python, R. Broadly speaking, you will have the opportunity
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) surveillance. Analyze large-scale data and summarize findings using statistical software (SAS, Python, R, and/or similar programs). Improve standardization, utility, and public health potential of data systems