Assistant Research Scientist

Organizational Summary Statement:

The Assistant Research Scientist will work as a Professional Track Research Faculty member in
the Department of Environmental Science & Technology (ENST) at the University of Maryland,
College Park (UMD). The primary objective of this person will be to characterize and assess
ecosystem service provisions associated with natural and restored wetlands within the Mid-
Atlantic region. This will include utilization of multi-sensor remote sensing data and application
of machine learning and deep learning methods, with the support of high-performance
computers. We are looking for candidates who have research experience in wetland/agricultural
ecosystems, exceptionally strong skills in GIS & remote sensing applications, and relevant
experiences in machine learning/deep learning modeling. This individual will assist in leading
collaborative research efforts with the USDA-ARS and other federal partners.

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.

Minimum 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.


Physical Demands:

Ability to occasionally perform indoor and outdoor work related to collection of soil and plant samples and related analyses, requires the lifting and carrying (up to 30 lbs.), standing, kneeling, bending, stooping, and reaching.

Licenses/ Certifications: N/A

No

AGNR-Environmental Science & Technology

Faculty Regular

$80,000 to $90,000