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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn
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. Experience in the use of good laboratory practice in collecting and managing analyses performed in a research study. Experience with statistical analysis (e.g., R or SAS software packages) of datasets. Point
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software platforms, smoke emission factors and total smoke production by factor will be accounted for and differenced for the range of burn conditions as above. This research will involve a collaborative
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in agricultural soil microbiology. The participant will also have active exposure to statistical data analytics using R, Python, and current bioinformatic software. The participant will gain or enhance
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have been received within the past five years. Preferred skills: Experience with ecological modeling, spatial analysis and statistics, ArcGIS Pro software, Python and R coding. Stipend $60,000.00
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gas and other energy resources, policy assessment methods, including economic and modeling skills, and computer software products Research experience Excellent written and oral presentation skills Both
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of federal land managers, have a few different way of modeling complex restoration treatments in the software. However there is not much guidance on which is most accurate, or how examples of calibrating