Post-Doctoral Positions in Remote Sensing of the Environment

We are seeking to fill two post-doctoral positions for a two-year project funded by the U.S. Department of Defense. The project is focused on using remote sensing data and machine learning models to support stormwater asset management and assess the downstream impacts of military installations on the environment. The two positions are described below and interested candidates should send an email and CV to the respective PI.

Position 1. Remote sensing to assess operations and maintenance status of stormwater best management practices at military installations. This project will seek to use remote sensing data and machine learning models to (1) identify plant growth and stress in stormwater practices, and (2) quantify sedimentation and hydraulic function of stormwater assets. Background in remote sensing, GIS, and hydrology is strongly preferred. Interested candidates should send a statement of interest and CV to Walter McDonald (walter.mcdonald@marquette.edu).

Position 2. Remote sensing and machine learning to assess and identify the impact of military installations on downstream environmental and water quality. This project will seek to: (1) assess the impacts of water-borne pollutants on vegetation phenology and performance across different environmental contexts (using satellite-derived data, e.g. MODIS, and existing vegetation datasets, e.g. NEON, FIA, ForestGEO); and (2) quantify downstream water quality and environmental impacts of human development, with a focus on military installations across the continental US (developing state-wide and US-wide models of water pollution and affects on vegetation communities and ecosystem processes). Background in remote sensing, GIS, and state-to-continental scale modeling is strongly preferred. Interested candidates should send a statement of interest and CV to Joseph LaManna (joseph.lamanna@marquette.edu).