Research Scientist – Texas

Texas A&M Natural Resources Institute
College Station, Texas
Job Category
Full time Positions
Commensurate with qualifications, State of Texas benefits, TRS retirement
Start Date
Last Date to Apply
The Texas A&M Natural Resources Institute (NRI) is looking for a motivated individual to join our team as a Research Scientist (permanent, non-tenure track) specializing in spatial analysis and species distribution modeling. Our strategic mission is to support natural resource management, conservation, policy, and extension efforts through scientific research, discovery, and the application of information technology. The selected individual will work with NRI researchers and TAMU faculty on all levels to develop and analyze complex spatial-temporal datasets relating to resource utilization, land use/land cover, hydrology, human demographics, habitat niche, species distributions, and sociological data to identify natural and anthropogenic variables that influence land use, natural resource policy, species, habitat, and trends. The successful applicant would be a key team member of the Texas Land Trends project, a cross-cutting NRI program that monitors and identifies the environmental and socio-economic drivers of land use trends in Texas ( Essential Duties · Provide leadership and expertise in spatial technologies, data management, and study design. · Demonstrate spatial analyses in teaching, research, and extension. · Conduct spatial data processing, analysis, reporting, and publications. · Assist with model development for all geospatial projects
Required Education and Experience: · Ph.D. in Natural Resources, Remote Sensing, Geography, Statistics or related field. · Experience in geospatial technology, spatial analyses, and spatial statistics. · Excellent communication skills and technical writing skills. · Good analytical and problem solving skills Required Special Knowledge: · Experience with GIS software such as ArcGIS, GRASS, TNTmips, and QGIS. · Experience with remote sensing software such as ERDAS, ENVI, TNTmips, GRASS, and R. · Proficient in the use of R, Python, SAS, STATA, and other tools for scripting statistical and spatial-temporal analyses. Preferred Education and Experience: · 4-8 years post-doctoral experience in geospatial technology, remote sensing, and spatial analyses. · Peer-reviewed publication record including use of spatial analyses. · Experience with proposal writing and securing external grant funding. · Experience with reproducible workflows and version control for code collaboration. · Familiarity with cloud-based platforms and high-performance computing facilities. To apply, please send a single PDF file that includes (1) cover letter describing your research interests, (2) a complete CV, and (3) the names and contact information for three professional references to Roel Lopez ( and Brian Pierce (
Contact Person
Roel Lopez
Contact eMail
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