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the guidance of your mentor, you will study Fusarium Head Blight (FHB), one of the most significant diseases affecting wheat production, grain quality, and food safety worldwide. You will learn how
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are highly desirable. Familiarity with data science and machine learning applications for analytical chemistry, industrial/agricultural facilities, and techno-economic or life-cycle analysis is considered a
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chronic conditions and illnesses. This research aligns with CVDB's public health mission to strengthen evidence supporting improved recognition and characterization of ME/CFS. Learning Objectives: You will
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nucleic acid extractions, amplicon sequencing, data management and analysis. You will learn how to identify risks and improvement opportunities, ensure compliance with established policies and agency
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interdisciplinary research teams on quantitative analyses of complex genomic datasets; Learn to use remote, high powered computer clusters to process large datasets. Mentor: The mentor for this opportunity is Adam
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., Medicare and Medicaid) to examine clinical and environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster
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for respiratory virus genomics; Final projects will be developed jointly by the mentor and fellow. Learning Objectives: During the fellowship, you will learn to: Apply bioinformatics and data science methods
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also receive training in use of Excel spreadsheets, PowerPoint, Visio, and plotting and statistical analysis using various software platforms. Learning Objectives: Under the guidance of a mentor you will
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MMA’s program and regional offices, exposing you to a variety of perspectives and issues. Learning Objectives: Under the guidance a mentor, you may gain skills and experience in the following areas: Gain
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. Learning Objectives: By the end of this training/research experience, you will be able to: Explain the structure and functional organization of plant, insect, and/or fungal genomes and describe how genomic