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and subsurface responses to environmental disturbances. Fellows will practice a variety of data collection, monitoring, and analysis techniques by collaborating on one or more of the following
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internal institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences
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responses to environmental disturbances. Fellows will practice a variety of data collection, monitoring, and analysis techniques by collaborating on the following research track: Post-Fire Hydrology and
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cDNA for next generation sequence (NGS) analysis and develop bioinformatic skills to analyze large sequence data sets. You will understand the complexities and application of NGS to inform on viral
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apply? Through active involvement in these projects, you will further develop your skills in data collection, analysis, and interpretation related to toxicants, resuscitative adjuncts, and biological
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financial and environmental costs and benefits of these practices. We will utilize data collected in a large-scale experiment on commercial farms near Clarksdale, MS to conduct a systems-level analysis of
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(e.g., enhancers, promoters) in cattle. Customize bioinformatics pipelines for automated processing and analysis of short- and long-read sequencing data. Apply computational approaches to detect genetic
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of the relevant fields. Preferred skills: Previous experience in computational ecology and statistics. R or Python. Statistical analysis tools such as NIMBLE, JAGS or STAN. Familiarity with data processing, quality
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climate. Observational work would include data from GRACE, SMAP, GPM or in-situ stations. Model diagnosis and analysis can include CLM, VIC, CLSM, and LIS frameworks including GLDAS and NLDAS. Model
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bioinformatics tools, pipelines, and statistical methods for the analysis of large-scale genomic and transcriptomic datasets ('big data'), with hands-on experience in high-performance computing (HPC) environments