Bioinformatics Analyst

Apply now Job no: 494288
Work type: Professional
Location: Oklahoma City
Categories: Technology/Research

Pay Range: Targeted pay range of $45,600 - $60,400 annually, depending on experience.

Benefits Eligible: Yes

Work Schedule: Monday – Friday, 8:00 a.m. to 5:00 p.m.

Travel: Not required

Position Introduction:

The Department of Molecular Genetics and Genome Sciences is seeking a Bioinformatics Analyst to join Dr. Jun Li's computational biology group. The selected candidate will support the growing volume of collaborative genomics and epigenomics projects in the Department of Molecular Genetics and Genome Sciences. The Bioinformatics Analyst will perform statistical and computational analysis of high-dimensional genomic/epigenomic data, interpret results in collaboration with investigators, and develop reproducible analytical workflows for technologies such as RNA-seq, ATAC-seq, single-cell, and spatial profiling.

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Required Education and Experience:

Bachelor's degree in a relevant field (e.g., Biology, Neuroscience, Biochemistry, or Microbiology with a computational focus; Computer Science with a biological focus; or a related discipline)

Hiring Contingent Upon a Background Check: Yes

Special Indications: Position subject to renewal based on availability of funds

Advertised: 15 Oct 2026 Central Daylight Time
Applications close: 13 Jan 2027 Central Standard Time

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Bioinformatics Analyst

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Position	Location	Closes
Bioinformatics Analyst	Oklahoma City	13 Jan 2027
The Department of Molecular Genetics and Genome Sciences is seeking a Bioinformatics Analyst to join Dr. Jun Li's computational biology group. The selected candidate will support the growing volume of collaborative genomics and epigenomics projects in the Department of Molecular Genetics and Genome Sciences. The Bioinformatics Analyst will perform statistical and computational analysis of high-dimensional genomic/epigenomic data, interpret results in collaboration with investigators, and develop reproducible analytical workflows for technologies such as RNA-seq, ATAC-seq, single-cell, and spatial profiling.