-
with cell culture techniques. R, Python, or other data science tools for microbiome analysis. Publication record in peer-reviewed journals. Preferred Qualifications Experience with colorectal cancer
-
bioinformatics tools for microbiome analysis (QIIME2, Kraken2, MetaPhlAn) and AMR gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments
-
. Additional Skills (Preferred): Experience with environmental data analysis (R, Python, multivariate statistics). Experience in GIS and ecological mapping. Strong scientific writing skills and command
-
sequencing (NGS) and omics data analysis. Knowledge of microbial ecology, dysbiosis, and host-microbiome interactions. Familiarity with cell culture techniques. R, Python, or other data science tools
-
programming (e.g., R, Python). Strong record of peer-reviewed publications in plant science or related fields. Excellent communication skills and ability to work in a collaborative, interdisciplinary team
-
gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments. Solid understanding of antimicrobial resistance mechanisms, horizontal gene