Postdoctoral Research Associate - Aquatic Remote Sensing

About the role

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.

Responsibilities

• 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.
• Conduct research applying remote sensing, drone image analysis, and machine learning to assess water quality parameters and physical properties of lakes and reservoirs.
• Develop, refine, and test computational workflows for processing and integrating multi-sensor datasets from satellite and UAV platforms.
• Implement and document quality-assurance procedures and validation protocols for environmental datasets.
• Prepare and submit manuscripts, progress reports, and conference presentations.
• Collaborate with faculty, students, and partner institutions on data synthesis and dissemination.
• Mentor undergraduate or graduate student researchers and contribute to proposal development for future research initiatives.

Requirements

• Ph.D. in Environmental Science, Remote Sensing, or a closely related field (awarded by start date).
• Demonstrated experience with satellite or drone remote sensing for environmental or aquatic systems.
• Proficiency in scientific programming (Python, R, or equivalent).
• Knowledge of machine-learning methods applied to environmental or geospatial data.
• Excellent writing, analytical, and communication skills, with a record of scholarly publications.

Qualifications

• Minimum qualifications: Ph.D. in Environmental Science, Remote Sensing, or a closely related field (awarded by start date).
• Preferred qualifications: Experience with Python-based cloud computing or high-performance computing environments, background in hydrology, limnology, or biogeochemistry, experience mentoring students and working within interdisciplinary research teams, ability to travel and present research at professional conferences.