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common laboratory equipment (e.g., autoclaves, sterilizers, centrifuges, homogenizers), and gain experience in DNA extraction, PCR amplification, and sequence analysis for Hemileia vastatrix and
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are not limited to: Collecting data using modern microbiological techniques Conducting statistical analysis Gaining experience utilizing software platforms Summarizing experimental findings by preparing
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. Developing the research or test methodology, executing the research protocol or test plan, data collection, data analysis, and reporting the findings. Conducting data analysis using engineering software and
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, and analysis of large, diverse datasets that benefit from high-performance computing (HPC) clusters. The objective of these fellowships is to facilitate cross-disciplinary, cross-location research
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cGMP conditions, microsatellite analysis, targeted sequencing, SNP analysis and WGS analysis. This combination of assays is extremely difficult to find. Furthermore, you will be conducting analyses using
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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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: 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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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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molecular and -omic methods. Learn advanced statistical and bioinformatic analysis of bulk and single cell transcriptomic data. Develop methods to link food nutrition environment with health outcomes. Learn