Postdoctoral Research Associate

RFCUNY Research Foundation of the City University of New York; United States; On-site; USD 65,000 - 72,000; Full time

Job summary

RFCUNY invites applications for a Postdoctoral Research Associate to join an interdisciplinary team focusing on aquatic remote sensing and machine learning. The position centers on developing computational workflows to study water-quality parameters in inland systems using satellite and UAV imagery.

The successful candidate will integrate multi-sensor data, validate methods, and contribute to publications, reports, and conference presentations, with opportunities to mentor students and

Qualifications

• 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.

Responsibilities

• Develop and validate methods for extracting surface temperature, optical water-quality indicators, and other parameters.
• Apply machine-learning tools for spatiotemporal analysis of aquatic systems.
• Contribute to data integration, QA procedures, and scholarly dissemination via publications and conferences.
• Collaborate with faculty, students, and partner institutions on data synthesis and proposal development.

Skills

Satellite remote sensing

Drone remote sensing

Scientific programming (Python/R)

Machine-learning for geospatial data

Scholarly writing & communication

Education

Ph.D. in Environmental Science/Remote Sensing or related field

Job description

Thank you for considering a career with the Research Foundation of The City University of New York (RFCUNY). The team at RFCUNY is made up of dedicated, talented professionals committed to providing the services that allow CUNY researchers, faculty, and staff to focus on their intellectual curiosity and scientific discoveries. We are pleased that you are interested in exploring opportunities to join RFCUNY.

Primary Location and Worksite

Primary Location: NYC COLLEGE OF TECHNOLOGY

Bargaining Unit: No

Worksite: New York City College of Technology, Brooklyn, NY

Institution Collaboration

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

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.

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.

Additional Information

Start Date: March, 1, 2026

Appointment Duration: One year, renewable contingent upon performance and funding availability.

Expected Travel: Occasional travel (12 times per year) to research meetings or scientific conferences.

Other Duties: Engage with the CUNY research community to support interdisciplinary collaboration. Assist with data curation, management, and documentation for consortium use. Perform other related duties as assigned.

Minimum Qualifications

• 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.

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.

Pay Range

Pay Range: $65,000 - $72,000

Benefits

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, pregnancy, childbirth, national origin, disability, marital status, veteran status, sexual orientation, gender identity, genetic information, marital status, domestic violence victim status, arrest record, criminal conviction history, or any other protected characteristic under applicable law.

About RFCUNY

The Research Foundation of The City University of New York (RFCUNY) is a nonprofit educational corporation founded in 1963 to provide post-award fiscal and administrative support for CUNY’s research and sponsored programs. RFCUNY’s services allow CUNY researchers, faculty, and staff to focus on their intellectual curiosity and scientific discoveries, on projects and programs that serve our local and global communities, proposing concrete solutions to society’s most pressing challenges. RFCUNY serves as a fiscal agent and works closely with all the CUNY campus Grants Offices to perform the core functions of post‑award financial management for CUNY research projects and sponsored programs.

These functions include legal assessment and signing of agreements where RFCUNY is named as a fiscal agent; setting up award accounts; preparing sub‑awards and assisting PIs in monitoring the work of the recipients of sub‑awards; supporting project directors with hiring and managing research project and sponsored program staff; supporting the purchasing and paying for goods and services with grant and program funds; managing financial aspects of projects including accounts receivable, financial reporting, invoicing, budget monitoring, and cost compliance with uniform guidance; ensuring that sponsor financial requirements are met; monitoring compliance with applicable project and financial management rules and laws; supporting the management of independent and external audits and financial reviews; and providing data, information, management expertise, and other supports to CUNY’s research and sponsored programs.