Assistant Research Scientist: Wetlands & AI for Ecosystems

University of Maryland; College Park (MD); On-site; USD 80,000 - 90,000; Full time

Job summary

University of Maryland, College Park, seeks an Assistant Research Scientist in ENST to characterize ecosystem services from wetlands using multi-sensor remote sensing and ML/DL methods. You will lead collaborative research with USDA-ARS and other partners, integrating lidar, optical, and radar feeds to model wetland dynamics in agricultural landscapes.

The role requires a Ph.D. in a relevant field, strong GIS/RS and ML/DL credentials, and a track record of publishing in top journals.

Qualifications

• Earned doctorate (Ph.D.) in ecology, biology, geography, or environmental science.
• Demonstrated expertise in combining GIS and Remote Sensing data with agroecosystem models to assess effects of agricultural conservation practices.
• Experience in classification of natural and agricultural ecosystems using machine learning and deep learning tools (minimum five years).
• Demonstrated experience with collection of field samples (soils, plants, etc.) for testing and evaluating model-based predictions.
• Experience in classification of wetland ecosystems using machine learning tools (minimum five years).
• Demonstrated ability to publish in scientific journals in the areas of Remote Sensing, GIS, Machine learning and Deep learning as applied to natural and agricultural systems.

Responsibilities

• Participate in development of collaborative research projects on mapping agricultural landscapes and assessing wetland status and ecosystem service provisions.
• Determine how to best facilitate the use of advanced machine learning/deep learning techniques in quantification of wetlands in agricultural landscapes.
• Integrate multi-sensor remote sensing datasets (e.g., lidar, optical, and radar) to initiate models designed to explore multi-scale wetland ecosystem dynamics and ecosystem service provision in agricultural landscapes as influenced by human activities.
• Develop and manage machine learning/deep learning models utilizing various remote sensing datasets with the support of high-performance computers.
• Develop deep learning workflows for generating topographic and landscape models that characterize complex agricultural watersheds using remote sensing datasets.
• Prepare presentations, reports, and publications of journal articles and communicate deliverables to sponsors.

Skills

GIS

Remote sensing

Machine learning

Deep learning

Field sampling

Publications

Education

PhD in ecology/environmental science

Tools

Python

R

MATLAB

Job description

University of Maryland, College Park, seeks an Assistant Research Scientist in ENST to characterize ecosystem services from wetlands using multi-sensor remote sensing and ML/DL methods. You will lead collaborative research with USDA-ARS and other partners, integrating lidar, optical, and radar feeds to model wetland dynamics in agricultural landscapes.

The role requires a Ph.D. in a relevant field, strong GIS/RS and ML/DL credentials, and a track record of publishing in top journals.