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Job ID: 132471

Postdoc in Computational Biology
University of Nebraska-Lincoln

Date Posted Oct. 28, 2019
Title Postdoc in Computational Biology
University University of Nebraska-Lincoln
Lincoln, NE, United States
Department Biological Systems Engineering
Application Deadline Open until filled
Position Start Date Available immediately
  • Post-Doc
  • Biology - Computational

The Song group at University of Nebraska-Lincoln, Lincoln, NE, is seeking highly motivated and enthusiastic postdoctoral scholars in the area of computational biology. Two positions are currently available to develop metabolic models and microbial interaction networks for natural and synthetic communities, and to predict their collective biochemical functions and responses to environmental perturbations. Postdoctoral investigators will closely collaborate with research teams at Pacific Northwest National Laboratory (PNNL), Richland, WA. Postdoctoral investigators will be responsible for helping meet project requirements and publishing papers in eminent peer-reviewed journals.
A PhD in Chemical Engineering, Biological Engineering, Computer Science, or related area is required. Expertise in at least one of the programming languages, such as Matlab, Python, R, Perl, C, C++, and C# is also required. Ideal candidates will have extensive experience in either: 1) metabolic network modeling and omics data integration, or 2) data-driven network inference (based on similarity-, regression-, or rule-based approaches). Experience in high-performance computing and dynamic modeling are preferred.
To view details of the position and make application, go to and click "Apply to this job" and complete the information form. Attach a letter of interest, curriculum vitae, and contact information for three professional references. Review of applications will begin December 2, 2019 and continue until the position is filled or the search is closed.
As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See

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