Hi there!
Woodwell is hiring a Research Associate to help build out a geospatial carbon model to scale over broad regions. The ideal candidate has experience working with large multitemporal raster datasets, developing optimized processing algorithms, and distributed computing in a cloud environment. A basic understanding of process-based models is a plus as well. Please reach out if you have any questions!
Summary:
Join Woodwell Climate’s Rangeland team as a Research Associate on a 2-year project focused on applying ecosystem carbon model simulations for conservation practices within U.S. rangeland systems, including those in Montana and Colorado. The successful candidate will work closely with our partners at the World Wildlife Fund and Columbia University, and will interact with ranch managers and other collaborators. The successful candidate will lead model simulations within a high-performance computing (HPC) environment, and may assist the team with model structural improvements, optimization, and parameterizations. The candidate will help process remote sensing and geospatial data, will lead model verification using field and lab data, will compute change detection analyses and data summary statistics. The successful candidate will develop reports for ranch managers, and will organize/co-lead a workshop in Montana for participating ranch managers.
Responsibilities include but not limited:
- Lead RangeSTAR model simulations within a HPC environment
- Mange very large geospatial datasets with a HPC environment
- Refine computing code (Python) and improve model parameter calibration
- Assist the team in developing an efficient pipeline for implementing the model across millions of acres
- Lead project reports/presentations
- Organize and lead a workshop for participating ranch managers
- Archive project data
Must have the Following Knowledge, Skills and Abilities:
- Minimum of 3 years of demonstrated a record of successful original research
- Cloud computing and HPC
- Experience improving and implementing process models
- Strong data science skills including proficiency in spatial data analysis
- Familiarity with different gridded geospatial data formats (NetCDF and Zarr)
- Experience using version control (Git, GitHub)
- Experience developing code within a Unix/Linux environment
- Strong coding skills using Python (R, Julia, C/C++ or other languages a plus)
- Superior oral and written communication and networking skills
- Ability to work as a member of a highly collaborative team in a fast-paced environment
- Willingness to travel about 5% of time
Qualifications:
- 3+ years’ experience with a Masters degree in Environmental Data Science, Earth System Science, Ecology, Geography, Environmental Engineering, Computer Science or a related discipline or 5+ years experience, appropriate for the requirements of the job with a bachelors degree or
- Ph.D. (granted or expected soon) in Environmental Data Science, Earth System Science, Ecology, Geography, Environmental Engineering, Computer Science or a related discipline