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    Opportunity: Researcher 6 @ University of Minnesota -- Minneapolis, MN (US)
    Submitted by Jill Hodsdon; posted on Thursday, September 28, 2017


    The osteosarcoma research group at the University of Minnesota seeks an experienced PhD-level bioinformaticist to lead and develop novel analyses of genomic data amassed locally from various sources. The group is highly collaborative, multi-disciplinary, and requires a skilled bioinformaticist to design and lead computational analysis of the osteosarcoma genome.


    Research design and implementation, manuscript preparation, grant writing


    • PhD in Biological Sciences, Bioinformatics, Computational Biology, Computer Science or related fields with substantial research and publication record
    • Experience in computational biology that spans multiple 'omics analysis platforms
    • Strong scientific understanding of molecular biology and genomics, with evidence of depth of understanding of experimental design and analysis
    • Experience with comparative genomics and integration of genomics and other "big data" matrices across species
    • Experience with statistical concepts such as dimension reduction, linear and nonlinear modeling, correlation, etc.
    • Familiarity with publicly available datasets such at TCGA, Roadmap Epigenomics and ENCODE/modENCODE
    • Fluency in one or more programming and scripting languages (such as Python, R, Perl, Matlab, C++ or Java)
    • A track record of achievement in the academic setting that includes presentations at national meetings and publications with evidence of publication of first author/co-first author in the peer reviewed literature
    • Documented evidence of excellent teamwork, time management and organizational skills


    Experience in/with the following:
    • Laboratory methods and bench (basic or translational) research
    • Cancer research, including a working understanding of computation approaches for cancer genome analysis
    • Developing algorithms for analysis of biological data
    • Algorithm development for analysis of massively parallel sequencing data (DNA-seq, RNA-seq)
    • Across platforms, such as genome-wide association studies, genome and transcriptome assembly from short read data, fusion gene discovery, DNA methylation analysis (probe based and bisulfite sequencing platforms), PacBio and isoseq technology to assemble novel transcriptomes, ATAC-seq, ChIP-seq and other enrichment based analysis, advanced visualization methods, and work in shared computing environments
    • Experience with a diverse range of data visualizations
    • At least two years of post-doctoral experience is highly desirable.


    Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.


    Minneapolis, MN




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    The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

    The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U:

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