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  • Bioinformatics Postdoc or Software Developer at UNC Charlotte, NC, USA

    The Luo Group at UNC Charlotte Dept. of Bioinformatics is seeking a Bioinformatics Postdoc or Software Developer. The new member will lead the development of bioinformatics web servers and applications. One focus is the Pathview project. Pathview is an open-source package that maps, integrates and renders a large variety of biological data onto pathways, and produces interpretable graphs with publication quality. Pathview was quickly adopted and widely used by thousands of scientists worldwide. With a major NSF grant recently awarded, Pathview will be fully developed as a systematic solution for pathway based analytics and visualization. First, Pathview Web server will be developed, which not only provides a graphic and user-friendly online portal to Pathview. Second, the Pathview R package will be expanded in its core functions to support better visualization and more data types. Third, multiple automated pathway analysis workflows will be developed based on Pathview for transcriptomic, genomic and other omics data analysis.
    For more information about the Pathview and related projects:

    Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.

    GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.


    Technical skills:
    LAMP based web + database development (PHP & JavaScript & MySQL preferred)
    Unix/Linux shell
    Python or Java
    Version control: svn and git
    Data integration and visualization
    R/Bioconductor is a plus, understanding molecular biology is a plus

    Other qualifications:
    Excellent communication and problem-solving skills, attention to detail
    Ability to work independently and in a team
    Self-motivated and disciplined, time and project management skills
    Enjoy building highly quality software/ Enjoy computational/statistical method development
    Proven research/development experience, publication records

    Education:
    PhD (or Master + 3 years working experience) in bioinformatics, computer science, statistics or related fields.

    Start Date:
    As soon as possible

    Application:
    Please send a CV, a cover letter and the names of 2-3 references to: [email protected]
    You may also include 1-2 representative papers/manuscripts.
    Last edited by bigmw; 08-12-2016, 04:54 PM.

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