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spectrometry, dynamic mechanical analyzer, thermogravimetric analysis, differential scanning calorimetry, and scanning electron microscopy Working knowledge of statistical analysis, data handling and data
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: The fellow will be involved in bioinformatics and statistical analysis in genetics
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scientists and communicate findings through manuscripts and newsletters. Learning Objectives: The candidate will have an opportunity to gain experience in plant genetic analysis, pipeline development, trait
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about: NGS library construction for genome and transcriptome sequencing. Marker-trait association analysis to identify genetic variations associated with important traits such as disease resistance and
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with digital PCR, multiplex PCR, and microbial community analysis required. Participant will also learn about statistical analysis of data in consultation with ARS colleagues. Participant will be a part
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Project: Under the guidance of a mentor, the participant will conduct research on targeted and non-targeted analysis of per- and polyfluoroalkyl substances (PFAS) in food and food contact materials
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metabolic changes during these events. Techniques may include using GC and LCMS for metabolic flux analysis using pathway labelling as well as analysis of changes in peel surface polymers due to cold chain
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: Conducting phenotype trials related to maize breeding and genetics. Marker-trait association analysis and RNA-Seq analysis to identify genetic variations associated with desirable traits Preparation of data
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characterization Knowledge of instruments including nuclear magnetic resonance, Fourier-Transform infrared, mass spectrometry, dynamic mechanical analyzer, thermogravimetric analysis, differential scanning
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analysis of projects relating to different aspects of vector biology, including ecology, population genetics, management strategies, virus interactions, and virus-transmission competence, depending