Intermittent Worker
Listed on 2025-12-11
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Research/Development
Biology, Research Scientist, Ecology
Apply now Job no: 510054
Position type: Intermittent Worker
Department: 080100 - FWRC - Forestry
Location: Main Campus - Starkville, MS
Categories: Support Staff, Intermittent Worker
Position Open Date: Dec 8 2025
The intermittent worker will support a research project aimed at understanding foliar-nutrient-related mechanisms influencing conelet abortion and survival in North American pine species. The role will involve quantitative analysis, mixed-effects modeling, and preparation of scientific manuscripts to support improved seed-orchard management and breeding recommendations.
Employees hired into Intermittent positions are limited to working no more than 720 hours per fiscal year.
The Department of Forestry is one of three departments in the College of Forest Resources and the Forest and Wildlife Research Center at Mississippi State University. The faculty have diverse teaching, research, service, and outreach expertise in the disciplines of forest biology and watershed management; forest economics, management, and policy; and forest measurements, biometrics, and spatial technologies. The Department has two undergraduate degree programs, Forestry and Natural Resource and Environmental Conservation, each accredited by the Society of American Foresters with ~200 students in addition to ~40 graduate students in both on-campus and distance education programs.
The University’s John W. Starr Memorial Forest (a +8,000-acre research and teaching forest), the Sam
D. Hamilton Noxubee National Wildlife Refuge, and the Tombigbee National Forest are located in close proximity to the University and used for teaching, research, and Extension/outreach activities. Mississippi State University is a Carnegie Very High Research Activity (R1) institution and a land grant university with a strong connection to the state-wide Extension Service. The University is in Starkville, a medium-size college town in northeast Mississippi ((Use the "Apply for this Job" box below).).
Appointment Date
December 2025.
Essential Duties and ResponsibilitiesThe successful candidate will assist the research team with the following tasks:
- Use mixed-effects modeling, multivariate statistics, and related quantitative approaches to analyze conelet abortion and survival patterns.
- Evaluate foliar nutrient concentrations, physiological traits, and environmental variables to identify drivers of conelet abortion and survival.
- Contribute to the preparation of a manuscript integrating key components of the project.
- Draft figures, tables, model summaries, and written sections as needed.
- Assist with literature synthesis and incorporation of peer-reviewed references.
- Maintain well-documented analytical workflows and reproducible code.
- Participate in periodic project meetings and provide progress updates.
- Perform other related duties as assigned to support the research objectives.
- Education:
High School Diploma. - Experience:
Relevant experience related to the essential duties and responsibilities listed above. - Substitutions:
An equivalent combination of related education and related experience may be considered for this position. - Must have a valid driver's license.
- Bachelor’s degree in forestry, biology, ecology, statistics, environmental science, or a related field.
- Graduate-level coursework or experience in mixed-effects modeling, multivariate statistics, or quantitative ecology.
- Demonstrated experience with statistical software (e.g., R).
- Strong quantitative skills and attention to detail.
- Ability to work independently and manage deadlines.
- Experience with tree physiology, seed orchards, forest genetics, or plant reproductive biology.
- Familiarity with R packages commonly used in mixed-effects and multivariate analysis (e.g., lme4, glmm
TMB, nlme, vegan, tidy models). - Experience preparing scientific manuscripts or reports.
- Work may involve moderate exposure to unusual elements, such as extreme temperatures, dirt, dust, fumes, smoke,…
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