Assistant Professor; Quantitative Microbe-Plant-Environment Interactions), Department of Microb

Assistant Professor (Quantitative Microbe-Plant-Environment Interactions), Department of Microbiology, Fall 2026

UTK

Sep 15, 2025

The Department of Microbiology at the University of Tennessee at Knoxville is seeking candidates for a nine-month, tenure-track faculty appointment at the Assistant Professor level applying quantitative approaches to study microbial (prokaryotic, eukaryotic, or viral) effects on plant ecosystems. Faculty in this position are expected to establish an innovative, externally funded research program and contribute to the departmental teaching and training mission at both undergraduate and graduate levels.

Candidates utilizing mathematical and/or computational approaches with or without wet-bench or field work are encouraged to apply.

Specific areas of interest include, but are not limited to:

• Modeling multi-omic data to quantify microbial metabolism, assembly, and their influence on native plant and/or agricultural systems
• Quantifying and predicting the sensitivity of the microbiomes of phototrophs to environmental change
• Developing quantitative tools for the analysis of plant microbiome systems data, including but not limited to, machine learning, metabolic modeling (e.g. flux-balance models), and network analyses
• Mathematical or statistical modeling of temporal and spatial variability to predict microbial effects in native plant and agricultural systems
• Development of ecological theory, for example to understand drivers of microbial community shifts associated with plant host phenotype or environmental perturbations

This position is part of a faculty cluster hire in Bioinformatics, Genomics and Quantitative-based Solutions for Food Security ((Use the "Apply for this Job" box below).). Recruitment into the cluster creates opportunities to build bold agendas that advance big ideas. The successful candidate will join an established UT Community of Scholars organized along the theme of Plant Resilience in a Changing Environment (PERCE-CoS). This is a team of approximately 25 successful faculty drawn from across campus that bring shared and complementary research interests in areas including, but not limited to, bioinformatics, data science, machine learning, microbiology, entomology, plant sciences, agricultural informatics, quantitative environmental change biology, as well as a strong desire to grow the scholarly and educational influence of their work.

The PERCE-CoS also offers a unique framework for professional development and mentorship with a rich transdisciplinary environment.

The University is beginning a next-level initiative aimed both at substantially elevating the University's national reputation for impactful research, scholarship, and creative activity and at assembling a roster of faculty committed to delivering one of the nation's best educational experiences for undergraduate and graduate students.

Competitive applicants will meet the minimum requirements of a PhD in a related field and at least two years of postdoctoral experience at the onset of the position. The successful candidate will have established a record of research that includes significant scientific advancements to their field, as evidenced through peer-reviewed publications and other contributions.

The successful candidate is anticipated to start this position August 1st, 2026. Evidence of prior formal or informal teaching and outreach will be an advantage. UTK is a land‑grant university, and values engaged forms of research/scholarship/creative activity, teaching and service, and considers evidence of these commitments in the records of applicants. Interested applicants should submit a (i) cover letter; (ii) CV;

(iii) contact information for at least 3 references; (iv) research statement describing accomplishments and future plans (3 pages, excluding references); (v) teaching philosophy (1 page) and (vi) two papers that best represent the applicant’s contribution to science/society along with a brief statement (1 paragraph per paper)…