Post-Doc Research Associate (Liu Lab)

University of North Carolina at Chapel Hill • Chapel Hill, NC

77d

About The Position

The Liu Lab at the University of North Carolina at Chapel Hill is seeking a highly motivated Postdoctoral Research Associate to investigate the evolutionary mechanisms that shape the pathogenicity and drug resistance of Mycobacterium tuberculosis (Mtb) and nontuberculous mycobacteria (NTM). This position will focus on identifying the genetic determinants that drive bacterial adaptation to the host environment and contribute to antimicrobial resistance and persistence during infection. The successful candidate will leverage large-scale longitudinal clinical cohorts and bacterial isolate collections obtained through collaborations. The research will involve developing and applying novel population-genomic and statistical frameworks to detect non-canonical forms of natural selection, adaptive convergence, and bacterial traits associated with transmission, virulence, and treatment outcomes. This position will require integration of multi-dimensional datasets including genomic, transcriptomic, phenotypic, and clinical metadata to elucidate how bacterial evolution influences disease progression and therapeutic response. The postdoc will have the opportunity to collaborate closely with computational biologists, microbiologists, and clinicians, and to contribute to the design of follow-up functional validation experiments.

Requirements

• Ph.D. in microbiology, genetics, computational biology, or a related field.
• Ph.D. or all but dissertation for Ph.D.

Nice To Haves

• Strong background in microbial genomics, evolutionary biology, bioinformatics, or computational biology.
• Interest in translational applications connecting bacterial evolution to clinical impact.
• Experience in bacterial genomics or evolution.

Responsibilities

• Investigate the evolutionary mechanisms of pathogenicity and drug resistance in Mycobacterium tuberculosis and nontuberculous mycobacteria.
• Identify genetic determinants driving bacterial adaptation to host environments.
• Develop and apply population-genomic and statistical frameworks.
• Integrate multi-dimensional datasets including genomic, transcriptomic, phenotypic, and clinical metadata.
• Collaborate with computational biologists, microbiologists, and clinicians.
• Contribute to the design of follow-up functional validation experiments.

Benefits

• Comprehensive medical and vision coverage.
• Paid leave.
• Benefits and services supporting professional development and a healthy work/life balance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Educational Services
• Education Level: Ph.D. or professional degree