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analytical methods for PFAS quantitative analysis using gas and liquid chromatography-mass spectrometry instruments, conduct research on screening and non-targeted identification of PFAS with high resolution
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cleaning, alignment, variant calling, and filtering is highly desirable. Experience on R scripting, analytical pipeline developing, and interpreting is desirable. Skills in GWAS, QTL, genomic selection, and
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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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modeling, economic evaluation, and surveillance to enhance analytical tools. Activities will focus on gaining hands-on experience and contributing to emergency preparedness and surveillance planning
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Skills: Strong analytical skills and demonstrated experience with statistical programing in R. Experience using geospatial data for landscape-scale research. Experience with Species Distribution Modelling