Sort by
Refine Your Search
-
, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
-
of the relevant fields. Preferred skills: Previous experience in computational ecology and statistics. R or Python. Statistical analysis tools such as NIMBLE, JAGS or STAN. Familiarity with data processing, quality
-
) data sets in R or Python as well as GIS software such as QGIS or ArcGIS Pro. Knowledge of US forest ecosystems and background in analyzing forest structure, stand dynamics, biodiversity, and/or other
-
pursuing a bachelor's degree in the one of the relevant fields anticipated to be received by May 31, 2027. Preferred skills: Experience with fire management, landscape ecology, programming (e.g., R or Python
-
, Geoscience, Soil Science, Physics, or related fields). Preferred skills: Commitment to contributing to outreach activities and research dissemination. Experience in computer programming (R+, Matlab, Python
-
(e.g., command-line interface, scripting in R/Python, use of common bioinformatics software). Strong foundation in experimental design, advanced statistical analysis, and scientific writing. Proven
-
/statistical skills Experience with statistical analysis software (e.g. R, SAS), GIS software (e.g., ArcGIS, QGis), and programming languages (e.g., R, Python, C++). Experience or interest in science integration
-
practices in the US agriculture. Proficiency in R, Python, Matlab, or other common programing languages (e.g., C/C++). Strong computational skills. Strong oral and written communication skills. Stipend
-
. Degree must have been received within the past five years or anticipated to be received by 5/31/2026. Preferred skills: R, Python, and Microsoft software Statistical analysis tools. Familiarity with ArcGIS
-
implementing and evaluating precision technologies. Experience in the use of scripting languages (e.g. python, R, etc.) Experience performing multivariate statistical analyses and using statistical analyses