University of Idaho
5 days ago Be among the first 25 applicants
Get AI-powered advice on this job and more exclusive features.
University of Idaho, Department of Soil and Water Systems
Position Overview
The University of Idaho seeks a Research Scientist to lead the development and implementation of advanced hydrologic, geomorphologic, and climate-driven models for the assessment of road-stream culvert vulnerability to post-fire flooding on National Forest lands. This position represents a critical expansion of the USDA-FS and DOT/FHWA-funded “CULVERT” project, extending applications to Forest Service sites in the Pacific Northwest and Southwest regions experiencing increasingly frequent and intense wildfires and extreme precipitation events. The researcher will lead the development of a fully dynamic, web-GIS-based interactive platform that integrates multiple computational models to predict culvert vulnerability to precipitation-driven flooding, post-wildfire debris flows, and geomorphologic hazards. Working in collaboration with USGS, National Forest Lands, USEPA, National Park Association, and academic partners, the selected candidate will create an automated decision-support tool that prioritizes culvert maintenance and redesign efforts to enhance infrastructure resilience. Primary Responsibilities
Lead model design, development, and validation of integrated hydrologic and hydro-geomorphologic prediction systems incorporating the WEPP model, peak flood discharge estimation, debris flow modeling, scour prediction, and sediment transport dynamics Develop and deploy full-stack web applications featuring real-time model execution, interactive geospatial visualization, and automated risk assessment workflows for culvert vulnerability analysis Process and integrate large-scale, multi-format datasets including high-resolution LiDAR-derived terrain data, soil moisture networks, hydrometeorological observations, and remote sensing products (satellite, radar, reanalysis) Design automated Extract Transform Load (ETL) pipelines for continuous ingestion and processing of climate, hydrologic, and geospatial data streams Synthesize research findings through peer-reviewed scientific publications, technical reports, and presentations to stakeholder agencies Collaborate with federal partners to ensure model outputs align with operational decision-making needs and infrastructure management priorities Develop interactive visualization tools and dashboards for non-technical end users to access model predictions and prioritize maintenance activities Coordinate with project scientists to assess project implications, analyze integrated datasets, and provide evidence-based recommendations for culvert design standards and maintenance protocols Attend conferences and publish research papers Required Qualifications
PhD in Hydrology, Water Resources Engineering, Earth System Science, Atmospheric Science, Civil/Environmental Engineering, or closely related field Advanced expertise in physics-based hydrologic modeling or WEPP at watershed to regional scales, including experience with precipitation-runoff modeling, flood frequency analysis, and extreme value statistics Demonstrated experience with climate and hydrologic data analysis, including handling of multi-format datasets (NetCDF, GRIB, HDF5, GeoTIFF) Strong programming proficiency in Python, including advanced use of NumPy, xarray, pandas, geopandas, and scientific computing libraries Proficiency in geospatial analysis platforms including ArcGIS, QGIS, GDAL, Google Earth Engine, or similar GIS environments Experience with high-performance computing environments, GNU/Linux systems, batch job management, and parallel processing workflows Excellent written and oral communication skills, with demonstrated ability to translate technical findings for diverse audiences including scientists, engineers, and natural resource managers Track record of scientific publication in peer-reviewed journals Preferred Qualifications
Experience with machine learning applications in environmental science, including ensemble methods or deep learning frameworks (PyTorch, TensorFlow, Keras) Knowledge of atmospheric dynamics, extreme precipitation events, and climate teleconnections relevant to flood hazard assessment Familiarity with post-wildfire hydrologic response, debris flow modeling, or fire-related geomorphic processes Knowledge of database management systems (MySQL, PostgreSQL, NoSQL) and version control systems (Git) and CI/CD workflows (GitHub Actions) Experience with statistical analysis in R, particularly for extreme value analysis and spatial statistics Proficiency with cloud computing platforms (AWS, Google Cloud) and containerization (Docker Compose, Kubernetes) Experience developing REST APIs and implementing real-time data pipelines Experience with Climate Data Operators (CDO), NCO, or other specialized climate data processing tools Background in soil science, geomorphology, or hydraulic engineering Experience working with federal land management agencies or transportation departments Application Materials
Complete applications must include: Cover letter addressing qualifications and research interests Relevant experience with hydrologic modeling and web application development and deployment Approach to integrating multiple model types for infrastructure vulnerability assessment Vision for translating complex model outputs into actionable management tools Contact information for three professional references This position will be based at the University of Idaho with close collaboration with federal partners at USDA Agricultural Research Service, USGS, and U.S. Forest Service offices. The appointment is full-time for an initial period of two years, with possibility of extension contingent upon project funding and performance. Seniority level
Mid-Senior level Employment type
Full-time Industries
Higher Education
#J-18808-Ljbffr
The University of Idaho seeks a Research Scientist to lead the development and implementation of advanced hydrologic, geomorphologic, and climate-driven models for the assessment of road-stream culvert vulnerability to post-fire flooding on National Forest lands. This position represents a critical expansion of the USDA-FS and DOT/FHWA-funded “CULVERT” project, extending applications to Forest Service sites in the Pacific Northwest and Southwest regions experiencing increasingly frequent and intense wildfires and extreme precipitation events. The researcher will lead the development of a fully dynamic, web-GIS-based interactive platform that integrates multiple computational models to predict culvert vulnerability to precipitation-driven flooding, post-wildfire debris flows, and geomorphologic hazards. Working in collaboration with USGS, National Forest Lands, USEPA, National Park Association, and academic partners, the selected candidate will create an automated decision-support tool that prioritizes culvert maintenance and redesign efforts to enhance infrastructure resilience. Primary Responsibilities
Lead model design, development, and validation of integrated hydrologic and hydro-geomorphologic prediction systems incorporating the WEPP model, peak flood discharge estimation, debris flow modeling, scour prediction, and sediment transport dynamics Develop and deploy full-stack web applications featuring real-time model execution, interactive geospatial visualization, and automated risk assessment workflows for culvert vulnerability analysis Process and integrate large-scale, multi-format datasets including high-resolution LiDAR-derived terrain data, soil moisture networks, hydrometeorological observations, and remote sensing products (satellite, radar, reanalysis) Design automated Extract Transform Load (ETL) pipelines for continuous ingestion and processing of climate, hydrologic, and geospatial data streams Synthesize research findings through peer-reviewed scientific publications, technical reports, and presentations to stakeholder agencies Collaborate with federal partners to ensure model outputs align with operational decision-making needs and infrastructure management priorities Develop interactive visualization tools and dashboards for non-technical end users to access model predictions and prioritize maintenance activities Coordinate with project scientists to assess project implications, analyze integrated datasets, and provide evidence-based recommendations for culvert design standards and maintenance protocols Attend conferences and publish research papers Required Qualifications
PhD in Hydrology, Water Resources Engineering, Earth System Science, Atmospheric Science, Civil/Environmental Engineering, or closely related field Advanced expertise in physics-based hydrologic modeling or WEPP at watershed to regional scales, including experience with precipitation-runoff modeling, flood frequency analysis, and extreme value statistics Demonstrated experience with climate and hydrologic data analysis, including handling of multi-format datasets (NetCDF, GRIB, HDF5, GeoTIFF) Strong programming proficiency in Python, including advanced use of NumPy, xarray, pandas, geopandas, and scientific computing libraries Proficiency in geospatial analysis platforms including ArcGIS, QGIS, GDAL, Google Earth Engine, or similar GIS environments Experience with high-performance computing environments, GNU/Linux systems, batch job management, and parallel processing workflows Excellent written and oral communication skills, with demonstrated ability to translate technical findings for diverse audiences including scientists, engineers, and natural resource managers Track record of scientific publication in peer-reviewed journals Preferred Qualifications
Experience with machine learning applications in environmental science, including ensemble methods or deep learning frameworks (PyTorch, TensorFlow, Keras) Knowledge of atmospheric dynamics, extreme precipitation events, and climate teleconnections relevant to flood hazard assessment Familiarity with post-wildfire hydrologic response, debris flow modeling, or fire-related geomorphic processes Knowledge of database management systems (MySQL, PostgreSQL, NoSQL) and version control systems (Git) and CI/CD workflows (GitHub Actions) Experience with statistical analysis in R, particularly for extreme value analysis and spatial statistics Proficiency with cloud computing platforms (AWS, Google Cloud) and containerization (Docker Compose, Kubernetes) Experience developing REST APIs and implementing real-time data pipelines Experience with Climate Data Operators (CDO), NCO, or other specialized climate data processing tools Background in soil science, geomorphology, or hydraulic engineering Experience working with federal land management agencies or transportation departments Application Materials
Complete applications must include: Cover letter addressing qualifications and research interests Relevant experience with hydrologic modeling and web application development and deployment Approach to integrating multiple model types for infrastructure vulnerability assessment Vision for translating complex model outputs into actionable management tools Contact information for three professional references This position will be based at the University of Idaho with close collaboration with federal partners at USDA Agricultural Research Service, USGS, and U.S. Forest Service offices. The appointment is full-time for an initial period of two years, with possibility of extension contingent upon project funding and performance. Seniority level
Mid-Senior level Employment type
Full-time Industries
Higher Education
#J-18808-Ljbffr