Opportunities by NSF Division

Much unsaturated-zone water moves not as typically slow diffuse flow, but rapidly through preferential flow channels such as root holes and fractures. Impacts are profound and far-reaching for issues such as contaminant transport, ecohydrology, and aquifer recharge. Understanding is limited and accepted theory is lacking, making preferential flow a crucial and exciting area of earth science.

The goal of this project is to contribute to our understanding of anelastic path attenuation in ground-motion prediction equations (GMPEs) by searching for correlations between seismic attenuation models constrained by 3D geophysical observations and \ ground motion measurements at individual stations.

Are you interested in communicating the value of science and technology? Are you excited about the use of Earth observations to help solve society's most pressing problems? If so, then come work with the USGS to advance the use of land imaging satellite observations with key stakeholders!

Northern New England is a fascinating landscape of conifers, unique wildlife, mountainous landscapes, and warming climates. Help us better understand whether red squirrel populations are responding to climate change and predict how that will impact the vulnerable boreal birds that they prey upon.

This interagency (USGS, FEMA, USACE) pilot project is a unique opportunity to investigate how to operationalize crowdsourcing and open innovation for emergency management through the standardization of data and tools. Help design a playbook, and organize workshops and hackathons with key innovators and open data experts across the government.

Have you ever thought that our nation’s satellites could be put to better use than watching you drink your fifth cup of coffee as you prepare for final exams? If so, then this is a project that you would enjoy. The hydrologic community is at a pivotal moment in the application of remote sensing into everyday decision making and we need you.

An opportunity to work with models of multivariate environmental and ecological processes from either a mathematical/statistical or scientific focus. The former would focus on elaborating current methods for making inferences or predictions from multivariate data while the latter would focus on using those current methods to better understand multivariate environmental or ecological processes.

South Florida’s proximity to sea level makes Miami and the Everglades ecosystem vulnerable to storm surge. Sediment cores document past rates of sea level rise, but past storm signatures are difficult to identify. Development of modern calibration datasets will provide information to interpret past storm records and help urban planners and resource managers prepare for the future.

The topic of how climate change will exacerbate the impacts of invasive species is at the cutting edge of conservation biology and applied ecology. We are looking for someone to work with a group of researchers and natural resource managers under the paradigm of translational ecology, producing publications and designing research that will improve conservation outcomes on the ground

We are inviting you to participate in an exciting project that brings together citizen science data from iNaturalist and other online platforms to improve currently static biodiversity databases. This project will ultimately identify invasive species, taxonomy changes, and potential climate migrants that will aid conservation efforts on public lands.

Augment existing near real-time earthquake-triggered landslide and liquefaction hazard models with products such as landslide dam likelihood, road network disturbances, and disruption to ports. Investigate methods for improving and/or rapidly updating models such as remote sensing data, historical fill maps, and social media and news reports.

The goal of this activity is to improve water security in the MENA region by accelerating ASR. This activity will accelerate adoption of ASR by applying and disseminating new methods for mapping and identifying high potential ASR locations using remote sensing, geospatial data, and hydrologic analysis.