Assistant Research Scientist

University of Maryland•College Park, MD

3d•$80,000 - $90,000

About The Position

The Assistant Research Scientist will serve as a Professional Track Research Faculty member in the Department of Environmental Science & Technology at the University of Maryland, College Park. The role focuses on characterizing and assessing ecosystem service provisions associated with natural and restored wetlands in the Mid-Atlantic region, using multi-sensor remote sensing data and machine learning and deep learning methods supported by high-performance computers. The successful candidate will bring research experience in wetland and agricultural ecosystems, strong GIS and remote sensing skills, and relevant machine learning and deep learning modeling experience. The position will help lead collaborative research with USDA-ARS and other federal partners. The work includes developing collaborative projects on agricultural landscape mapping and wetland assessment, integrating lidar, optical, and radar remote sensing datasets, and building models and workflows to investigate wetland dynamics and ecosystem services in agricultural landscapes. The position also prepares presentations, reports, and journal publications and communicates deliverables to sponsors. Occasional indoor and outdoor fieldwork for collecting soil and plant samples and related analyses is required. Candidates must be eligible to work in the United States at hiring; the department will not provide work-visa sponsorship.

Requirements

Earned Ph.D. in ecology, biology, geography, or environmental science.
Demonstrated expertise combining GIS and remote sensing data with agroecosystem models to assess the effects of agricultural conservation practices.
At least five years of experience classifying natural and agricultural ecosystems using machine learning and deep learning tools.
Demonstrated experience collecting field samples, such as soils and plants, to test and evaluate model-based predictions.
At least five years of experience classifying wetland ecosystems using machine learning tools.
Demonstrated ability to publish scientific journal articles on remote sensing, GIS, machine learning, and deep learning as applied to natural and agricultural systems.
Must be eligible to work in the United States at the time of hiring; the department does not provide work-visa sponsorship.

Nice To Haves

Three years of experience using high-performance computing tools.
Three years of expertise in GIS and remote sensing support techniques and programming skills, including Python, R, or MATLAB.
Three years of experience managing models using varied remote sensing datasets and high-performance computers, especially deep learning tools.
Demonstrated familiarity with USDA conservation programs and conservation practices within the purview of CEAP.

Responsibilities

Participate in developing collaborative research projects on mapping agricultural landscapes and assessing wetland status and ecosystem service provisions.
Determine how to facilitate the use of advanced machine learning and deep learning techniques to quantify wetlands in agricultural landscapes.
Integrate multi-sensor remote sensing datasets, including lidar, optical, and radar, to develop models exploring multi-scale wetland ecosystem dynamics and ecosystem service provision in agricultural landscapes as influenced by human activities.
Develop and manage machine learning and deep learning models using various remote sensing datasets with high-performance computers.
Develop deep learning workflows to generate topographic and landscape models characterizing complex agricultural watersheds using remote sensing datasets.
Prepare presentations, reports, and journal publications, and communicate deliverables to sponsors.