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    This position is located in the Office of the Chief Information Officer (OCIO) Office of Research Computing (ORC). The Office of Research Computing provides a suite of services to researchers across the Smithsonian. This position is focused on methods such as developing computational algorithms and workflow pipelines to support biodiversity genomics and machine learning research and sophisticated statistical analysis that allow researchers to model the interaction of environmental conditions.

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    • Applies software tools and machine learning models used by biodiversity genomics and informatics researchers in order to carry out software analysis, modification and implementation to modify and enhance workflows for scientific researchers. These tools include Trinity, Canu, GATK, BLAST, JBrowse, WebApollo, and TensorFlow and PyTorch models.

    • Implements and enhances programs using modern programming languages (e.g. Python, Perl, Java, C++, C), statistical packages (e.g. R), and algorithms for mathematical modeling and implementing them in environmental science and machine learning pipelines and workflows that deliver the desired analysis of their data.

    • Uses high throughput sequencing technologies including PacBio, Illumina, and Oxford Nanopore to analyze data for biodiversity genomics research and informatics research.
    • Works closely with the IT professionals who manage, implement, test and debug the high-performance computing cluster (HPCC) and networking infrastructure, acting as translators and advocates for the research community to ensure the appropriate evolution of the technical infrastructure that underlies the research environment Smithsonian-wide. This includes using Unix/Linux shell scripting, as well as configuring the high- performance computing environment and the Univa Grid Engine job scheduler.

    Travel Required

    25% or less - Travel required is 25% or less of the time.

    Supervisory status


    Promotion Potential

    13 - FPL-GS-13

This job originated on www.usajobs.gov. For the full announcement and to apply, visit www.usajobs.gov/GetJob/ViewDetails/608401400. Only resumes submitted according to the instructions on the job announcement listed at www.usajobs.gov will be considered.