Assistant/Associate Professor in Food Microbiology
Listed on 2026-01-24
-
Healthcare
Public Health, Health Science -
Education / Teaching
Public Health, University Professor, Health Science, Academic
Overview
The NC State University Department of Food, Bioprocessing and Nutrition Sciences (FBNS) seeks applications from highly qualified scientists for a tenure-track, assistant/associate professor position in food microbiology. A Ph.D. in Food Science / Microbiology / Public Health or related field with microbiology experience is required. Experience with research related to food microbiology, including a track record of publications, grant writing, and mentoring is required.
Responsibilities- Develop both research and teaching programs
- Research program should be nationally-recognized and funded through applied research in critical data gaps, new technologies, and stakeholder needs in the area of food microbiology
- Mentor undergraduate, graduate students, and post-docs in research
- Teaching expectation is 1-2 graduate/undergraduate courses per year in the area of food microbiology
For the full announcement and to apply online, visit: (Use the "Apply for this Job" box below)./226449
QuestionsQuestions? Contact Dr. Clint Stevenson, ,
Equal OpportunityNC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran. Individuals with disabilities requiring disability-related accommodations in the application and interview process should contact Fred Jimenez, fmjimene, .
fbns.ncsu.edu
- Ph.D. in Food Science / Microbiology / Public Health or related field is required or related field with microbiology experience
- Prefer industry, postdoc and/or teaching experience
- Experience with advanced microbiological methods (bioinformatics, managing large data sets) is preferred
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