Post-Doctoral Research Associate: Department of Microbiology - UTK

University of Tennessee • Knoxville, TN

2d • $50,000 - $55,000 • Onsite

About The Position

The Zachary Burcham Lab in the Department of Microbiology at the University of Tennessee, Knoxville (UTK) is focused on how key microbes within host and environmental microbiomes degrade organic wastes and how modulating these microbiomes may lead to cleaner, more efficient waste conversion into valuable bioproducts. Current lab research spans diverse biological scales, including the microbial roles in organic waste cycling by the black soldier fly larvae (BSFL) gut microbiome, forensic microbiology, and collaborations in human health focused on oral and vaginal microbiomes. We utilize a combination of environmental sampling, laboratory models, multi-omics, and bioinformatic tools to explore the relationship between microbial diversity, microbial interactions, and ecological outcomes in free-living and host-associated systems. We are looking for a Postdoctoral Researcher to lead and advance computational/bioinformatic integrative analyses of these multi-omic microbiome datasets. A successful candidate will be able to develop reproducible analytical workflows, generate publishable insights from large, complex datasets, and contribute to high-impact manuscripts and grant proposals in host-associated and environmental microbiome research. This is a 12-month appointment renewed annually; funding is available for up to three years, with possible extension based on performance and funding.

Requirements

• Education: PhD (or equivalent doctoral degree) in bioinformatics, computational biology, microbiology, genomics, biostatistics, or a closely related field by the start date.
• Experience: Demonstrated experience analyzing microbiome sequencing data, including hands-on work with common microbiome data science pipelines and outputs.
• Wet-lab experience relevant to microbiome and host-associated systems, including molecular biology workflows (nucleic acid extraction, PCR/qPCR, NGS library preparation).
• Knowledge, Skills, Abilities: Strong programming/scripting skills (R and/or Python required; comfort in Linux/Unix environments).
• Experience working on HPC or cloud computing environments and managing computational jobs/workflows.
• Familiarity with microbiome methods and tools for taxonomic/functional profiling, assembly and binning, and statistical analysis.
• Ability to communicate results clearly (written and oral) and to work collaboratively in a team setting.

Nice To Haves

• Education: Formal training in advanced statistics, machine learning, or multi-omics integration is a plus. Preference for candidates with training in entomology, microbial degradation, or agricultural science.
• Experience: Experience with metatranscriptomic processing/analysis (e.g., rRNA filtering/depletion strategies, mapping/quantification, differential expression).
• Experience recovering and analyzing MAGs (e.g., bin refinement, quality assessment, dereplication, phylogenomics).
• Experience integrating metabolomics/chemical profiling or other multi-omics with microbiome sequencing data.
• Experience building robust, shareable pipelines with reproducible documentation practices.
• Wet-lab experience in vitro experimentation and/or hands-on work with entomology, decomposition/degradation-focused studies, or other related biological systems.
• Knowledge, Skills, Abilities: Strong quantitative skills in experimental design and statistical modeling for high-dimensional microbiome data.
• Interest in microbial ecology and host-microbiome systems (including insect- or decomposition-associated microbiomes) and translating analyses into biological insight.
• Demonstrated record of peer-reviewed publications and ability to independently drive projects to completion.

Responsibilities

• Lead bioinformatic analyses of microbiome datasets, including 16S rRNA, shotgun metagenomics, and metatranscriptomics (e.g., QC, assembly, binning/MAG recovery, annotation, and downstream statistical analyses).
• Develop, document, and maintain reproducible pipelines.
• Integrate multi-omic data with experimental and environmental metadata.
• Apply rigorous statistical and computational approaches for microbiome community ecology (diversity, ordination, differential abundance, compositional methods, network/assembly modeling as appropriate).
• Generate high-quality figures, tables, and reports suitable for manuscripts, conference presentations, and progress reports.
• Collaborate with PIs, students, and external partners; contribute to manuscript preparation and, as appropriate, proposal development.
• Mentor graduate and undergraduate trainees.
• Maintain accurate project documentation, data organization, and analysis provenance consistent with open and reproducible science.

What This Job Offers

• Education Level: Ph.D. or professional degree