Aquatic Remote Sensing

Applicants will be considered based on their knowledge, skills or abilities related to project needs. Specifically, applicants should have: demonstrated critical thinking and problem-solving abilities, curiousity and interest in learning new things, and a background in environmental science, remote sensing, geography, oceanography, hydrology, or computer/data science and an interest in applied environmental monitoring. Familiarity with GIS, satellite imagery, or water quality concepts is a plus but not required. The government-wide "Semester of Service" Student Volunteer Program, as authorized under 5 U.S.C §31114 and 5 CFR Part 3085, enables Federal agencies to engage students in unpaid, project-based assignments of limited duration. These assignments are designed to align with each agency's strategic priorities, offering participants practical experience within Federal operations while supporting the advancement of targeted initiatives. Make an impact while you learn. The Semester of Service Program offers students a volunteer project-based opportunity to support real Federal missions, gaining hands-on experience and valuable career-ready skills. With this project, you'll support a remote sensing-based project to help improve scientific understanding of water quality and water color.

• Work Schedule and Flexibilities: 10 hours per week for a full academic term (quarter or semester). Hours per week are flexible based on student's schedule and goals. Preferred hybrid but remote work is also an option. Project Description: Remote Sensing Algorithm Development for Water Quality Monitoring in San Francisco Bay. San Francisco Bay is an economically and environmentally important estuarine system where water quality is dynamic and highly variable. USGS scientists are developing and validating satellite-based algorithms to monitor water quality constituents - including suspended sediment, chlorophyll-a, and dissolved organic matter - using publicly available imagery from Landsat, Sentinel-2, and the new NASA PACE satellite. The student volunteer(s) will support this work by contributing to algorithm testing, validation, and development under the supervision of USGS research scientists. Core tasks may include: Compiling and processing satellite imagery and in-situ water quality datasets using Python Testing published remote sensing algorithms against field measurements from San Francisco Bay Supporting development of novel retrieval approaches, potentially including machine learning methods Contributing to map product generation or validation summaries