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/or high-throughput data processing generated by NGS sequencing, HPLC/MS techniques, or digital phenotyping systems. Familiarity with computational and bioinformatics tools such as R, Python
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conduct. Additional assets will include: Knowledge of programming languages R and/or Python for the purpose of biological, bioinformatic, and statistical data analysis, including the use of libraries
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IF>10; Proficiency in English (speaking and writing); Skills in data analyses using statistical (R or Python) or geoinformatic (QGIS or ArcGIS) software; Readiness to participate in scientific expeditions
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ecological genetics; 3. Hands-on experience in data analysis using the R programming environment; 4. Additional assets include experience with whole-genome sequencing (WGS) data analysis and methods in
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, pancreatic physiology, genome editing, high-throughput screen, or multiomics Knowledge of R, Seurat package or experience in transcriptomic data analysis Selection process The competition committee begins