Job:Clinical & Research Genomics Analyst
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6.7 years ago
chenzler • 0

Clinical & Research Genomics Analyst

As part of a joint initiative with the Department of Laboratory Medicine and Pathology (LM&P), the Research Informatics Solutions (RIS) team within the University of Minnesota Supercomputing Institute (MSI; is hiring a full time bioinformatics analyst to support clinical and research genomics at the University of Minnesota. The established RIS group at MSI is designed specifically to foster cutting edge collaboration between bioinformatics analysts and life sciences researchers and to leverage the rich computational and knowledge environment offered by the MSI and the University. LM&P and MSI have had a mutually beneficial partnership in diagnostics since 2011.

The successful applicant will join the expanding RIS team, currently composed of six informatics analysts plus three analysts partnered with LM&P. Successful candidates will have excellent communication skills, a strong analytical/computational background combined with demonstrated life sciences analyses experience, be highly organized, and comfortable working as part of an interdisciplinary research team on multiple projects.

As part of an interdisciplinary team, the successful candidates will have the responsibilities to:

  • Serve as a primary analyst and developer for clinical bioinformatics and research support for LM&P.
  • Serve as a liaison and informatics analyst for the LM&P faculty.
  • Carry out consultative informatics services and research for LM&P faculty on primarily molecular clinical research endeavors.
  • Design appropriate informatics strategies as required.
  • Develop, prototype, and execute analytic workflows.
  • Identify external resources that may be applied to challenges facing the interdisciplinary group.
  • Help to integrate new molecular technologies as they become useful for clinical purposes (e.g., single-cell expression profiling)
  • Appropriately document work conducted, both to comply with RIS reporting requirements, and to allow the preparation of any analytic reports required by the principal investigator of the project.

The ideal candidates will have advanced knowledge of next generation sequencing technologies with demonstrated practical experience in developing and carrying out analytical strategies in the context of NGS applications (e.g. DNA SNP and structural variant detection, de novo sequencing, RNA-seq).

Required Qualifications:

  • Doctorate in computer science with significant bioinformatics experience, or doctorate in the life sciences with significant programming experience.
  • 1+ year of work experience in the life sciences as primary or secondary research field
  • Hands on experience in developing and carrying out data analytical strategies and pipelines in the context of genomics.
  • Experience in handling and analyzing large data sets from high-throughput platforms such as next generation sequencing is a must.
  • Experience and general proficiency with use of web services, and statistical languages (e.g. R, SAS, MATLAB) plus currently used tools (e.g. BWA, TopHat, GATK)
  • Strong general computational and programming skills (Perl, Python, Java, C/C++), database programming skills (MySQL, PostgreSQL, Oracle) and competence with UNIX shell environment.
  • Must be able to understand and translate life scientist researchers' scientific goals into analytical strategies and process requirements.
  • Must be able to function as part of an interactive team while demonstrating self-initiative to achieve project's goals and group's mission.
  • Excellent oral and written English communication and inter-personal skills
  • Must be able to begin employment within 6 weeks of offer.

Preferred Qualifications:

  • 3+ years of experience in the life sciences as primary or secondary research field
  • Research background in genomics, genetics, molecular biology or computational biology
  • Research background in human or mammalian genetics strongly preferred
  • Experience with Next Generation Sequencing genomics research applications, data analysis and data management
  • Critical and independent thinking
  • Data modeling skills are highly desirable.

A portion of moving expenses will be covered per University guidelines.

Offers of employment are contingent upon the successful completion of a background check.

The University of Minnesota is an equal opportunity educator and employer.

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