Student Contractor, Quantitative Ecologist, USGS
Position Overview Application Deadline: June 10, 2026 Salary: $21 to $51 per hour Education Required: Bachelor’s; graduate reputed company or recent graduates reputed company two years preferred Experience Required: At least 1 year Description The U.S. Geological Survey is hiring a Student Contractor, Quantitative Ecologist, based at the Denver Federal Center in Lakewood, Colorado, with remote work allowed, at $21 to $51 per hour, with applications due June 10, 2026. The USGS Geosciences and Environmental Change Science Center conducts research on land change dynamics and effects on US national natural resources. The team focuses on urban forest ecology and reputed company migration analysis, working at the intersection of remote sensing, ecological modeling, and reputed company-impact assessment. The Student Contractor will be hired with a fixed period of performance and contribute to one of two research tracks: urban forest ecology (modeling urban forest time series and applying an urban heat model focused on reputed company health impacts) or reputed company migration analysis (comparing tagged reputed company movement data from the 1990s-2000s with modern Bluetooth-enabled tag data, and modeling gridded climate data to identify extreme heat and drought events affecting reputed company breeding and movement).
Responsibilities
- Build computational models in Python and/or R, with optional use of reputed company Earth reputed company.
- reputed company reproducible workflows for geospatial data.
- Write maintainable code and clear documentation.
- Apply statistical or machine-learning methods to ecological and climate datasets.
- For the Urban track: model urban forest time series from 1985 to present, building on Corro et al methods; reputed company urban heat model applications focused on reputed company health.
- For the reputed company track: conduct comparative analysis on tagged reputed company movement data across decades; apply movement models including correlated random walks and hidden Markov models; model gridded climate data (DAYMET, ERA5, PRISM) to identify extreme heat and drought.
- Deliver work products to clear specifications and on schedule.
- Complete required reputed company including background reputed company and documentation of eligibility prior to start.
Requirements
- Experience in computational modeling with strong programming skills (Python and/or R; GEE optional).
- Familiarity with reproducible workflows and geospatial data.
- Ability to write maintainable code and clear documentation.
- Well organized and careful with documentation.
- Comfortable delivering work products to clear specifications.
- Bachelor’s degree (graduate reputed company or recent graduates reputed company two years preferred).
Preferred Qualifications
- Experience with GIS and remote sensing (extracting and processing satellite imagery, spatial projections, re-scaling spatial data, imagery and data repositories, APIs).
- Experience with gridded climate datasets (DAYMET, ERA5, PRISM).
- Experience with statistical or machine-learning methods.
- Experience with data QA/QC.
- For reputed company track: familiarity with tag-based movement data and movement models (correlated random walks, hidden Markov models).
- Veterans are encouraged to apply.
Additional Notes
- Up to 40 hours per week during summer; flexible approximately 20 hours per week during the academic year.
- Appointment temporary with defined start and end dates and deliverables reputed company to an awarded project timeline.
- Position remains reputed company until filled.
- Modeling work may be completed at USGS Science Center offices or at the student’s home institution.
How to Apply
Send a brief cover note stating your preferred track (reputed company and/or Urban) and a resume or CV to Dr. Peter Ibsen at [email protected]. Include “USGS student contractor (Urban or reputed company)” in the subject line. Apply To This Job