The Center for Remote Sensing and Earth System Sciences (ReSESS)- City Tech, in collaboration with the Research Foundation of the City University of New York (RFCUNY), seeks a highly motivated Postdoctoral Research Associate to join an interdisciplinary research team focused on aquatic remote sensing and machine learning. The successful candidate will develop and apply advanced computational and remote-sensing approaches to study water-quality parameters and physical properties of inland aquatic systems using both satellite and drone-based imagery.
This position supports a collaborative research effort involving City Tech and external partner institutions. The project integrates multi-sensor data from satellites (e.g., Landsat, Sentinel-2) and unmanned aerial vehicles (UAVs) to improve understanding of how surface-water characteristics vary in response to climatic, geomorphological, and ecological factors. Research activities include the development and validation of methods for extracting and analyzing surface temperature, optical water-quality indicators, and other physical parameters, as well as the application of machine-learning tools for spatiotemporal analysis.
The Postdoctoral Research Associate will also contribute to data integration, quality assurance procedures (QAPP/DUAR standards), and scholarly dissemination through peer-reviewed publications, technical reports, and conference presentations.
Responsibilities include:
Additional Information:
Other Duties:
Minimum Qualifications:
Preferred Qualifications:
Pay Range: $65,000 - $72,000
RFCUNY Benefits RFCUNY Employee Benefits and Accruals
Equal Employment Opportunity Statement The Research Foundation of the City University of New York is an Equal Opportunity/Affirmative Action/Americans with Disabilities Act/E-Verify Employer. It is the policy of the Research Foundation of CUNY to provide equal employment opportunities free of discrimination based on race, color, age, religion, sex, national origin, disability, marital status, veteran status, sexual orientation, gender identity, genetic information, or any other protected characteristic under applicable law.
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