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with single-cell RNA-seq analysis. Experience with multi-omics integration and systems biology approaches. Familiarity with cloud computing, high-performance computing clusters, and machine learning
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technical progress reports to research sponsors. -Ensures program has sufficient and efficient computing capabilities (high performance research computing, workstations, software, network attached
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geospatial and scientific computing tools (e.g., Python, R, GIS, Google Earth Engine, or equivalent) to handle and process complex datasets. Excellent written and verbal communication skills, including the
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computing systems. Curates reference sequence databases and benchmarks pipeline performance using mock communities, reference materials, and cross platform comparisons. Manages sequencing data, metadata
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reproducible Linux/R/Bash workflows on high-performance computing resources for read quality control, assembly, binning, gene prediction, annotation, differential expression, and statistical analysis