Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
Loading job details
Assistant Research Scientist
- Type
- Full time
- Posted
- 14D AGO
About the role
Job Description SummaryOrganizational 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/AAdditional Job Details
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/AAdditional Job Details
Preferred Qualifications:
● Experience in using High-Performance computing tools (three years preferred).
● Expertise in GIS/remote sensing support techniques and programming skills including python/R/MATLAB languages (three years preferred).
● Experience managing models utilizing various remote sensing datasets with the support of high-performance computers, and especially deep learning tools (three years preferred).
● Demonstrated familiarity with USDA conservation programs and with specific conservation practices falling within the purview of CEAP.
Required Application Materials: (1) a cover letter, (2) a current CV or resume, and (3) contact information for three references
Best Consideration Date: 10/29/2026
Posting Close Date: 10/29/2026
Open Until Filled: N/A
Candidate must be eligible to work in the United States at the time of hiring. The department will not provide sponsorship for work-visa requirements.
Financial Disclosure RequiredNoFor more information on Financial Disclosure, please visit Maryland's State Ethics Commission website.
DepartmentAGNR-Environmental Science & TechnologyWorker Sub-Type Faculty RegularSalary Range$80,000 to $90,000Benefits SummaryFor more information on Regular Faculty benefits, select this link.
Background ChecksOffers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.
Employment EligibilityThe successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.
EEO StatementThe University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy.
Title IX Non-Discrimination NoticeResourcesLearn how military skills translate to civilian opportunities with O*Net Online
There are some positions that are not advertised on this career site as the search is being managed by a Search Firm.
Please visit the link below to see these available opportunities:
Similar roles
Research Assistant I LabHarvard Business School · Boston
Research Assistant I LabHarvard Graduate School of Education · Boston
Research Assistant I LabHarvard Kennedy School · Boston
Research Assistant I LabHarvard Kempner Institute · Boston
Research Assistant I LabBerkman Klein Center for Internet & Society · Boston
Research Assistant I LabHarvard Library Innovation Lab · Boston