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Postdoctoral Research Associate: GeoAI and Remote Sensing for Invasive Species Ecology
Job no: 537559
Work type: Post Doc Associate
Location: Main Campus (Gainesville, FL)
Categories: Computer Science, Grant or Research Administration, Artificial Intelligence, Physical/Mathematical Sciences
Department:16220000 - LS-GEOGRAPHY
Classification Title:
Postdoctoral Associate
Classification Minimum Requirements:

• A Ph.D. (by the start date) in Remote Sensing, Geography, Biology, Geospatial Science, Environmental Science, Ecology, or a closely related field.
• Demonstrated expertise in processing and analyzing remote sensing data (hyperspectral and/or Lidar is a strong plus).
• Strong proficiency in programming, particularly in Python and GEE for geospatial analysis and data science.
• Experience with machine learning/deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image or geospatial data.
• A track record of first-author publications in peer-reviewed journals.
• Excellent communication, collaboration, and writing skills.

Job Description:
The Geospatial Artificial Intelligence (GeoAI) Lab at the University of Florida, led by Dr. Di Yang, is seeking a highly motivated Postdoctoral Research Associate to join a new, multi-institutional research project focused on the invasive grass Ventenata dubia (VEDU). This project is a collaboration with leading experts at the University of Montana (Spatial Analysis Lab) and Boise State University.
The successful candidate will lead the development and implementation of cutting-edge remote sensing and machine learning techniques to address critical questions about invasive species surveillance and invasion dynamics. Key research themes include: 1) characterizing invasion resistance, 2) assessing the role of phenotypic plasticity in its competitive success, and 3) developing robust methods for spectral phenotyping using ground, drone, and satellite-based sensors. This position offers a unique opportunity to work at the intersection of remote sensing, spectranomics, genetic analysis, GeoAI, and invasion ecology within a dynamic, collaborative team.
Responsibilities:

• Design and lead remote sensing data acquisition campaigns using multi-scale platforms, including ground-based spectrometers, UAVs (optical, Lidar), and satellite imagery (e.g., Planet, Sentinel, Landsat).
• Develop and apply advanced machine learning and deep learning models (GeoAI) for fusing, analyzing, and interpreting multi-sensor data to track invasion species patterns
• Create novel analytical workflows to build calibration equations for discriminating VEDU from other co-occurring grass species.
• Integrate remote sensing-derived products with in-situ ecological data (e.g., canopy cover, height, alpha diversity, chemistry, soil texture, disturbance intensity) to model invasion dynamics and resilience across landscapes.
• Collaborate closely with project partners to synthesize findings and build follow-on funding opportunities.
• Lead the preparation of high-impact, peer-reviewed publications.
• Present research findings at national and international scientific conferences.
• Mentor graduate and undergraduate student in the GeoDI (Geospatial Digital Informatics) Lab.

UF is the state's oldest, largest, and most comprehensive land grant university with an enrollment of over 50,000 students and was ranked 7th in the country among public universities (US News and World Report 2025 rankings), and 1st among public institutions in the Wall Street Journal 2023 survey. UF is located in Gainesville, a city of approximately 150,000 residents in North-Central Florida, 50 miles from the Gulf of Mexico, and 67 miles from the Atlantic Ocean, and within a 2-hour drive to large metropolitan areas (Orlando, Tampa, Jacksonville). The beautiful climate and extensive nearby parks and recreational areas afford year-round outdoor activities, including hiking, biking, and nature photography. UF's large college sports programs, museums, and performing arts center support a range of activities and cultural events for residents to enjoy. Alachua County schools are highly rated and offer a variety of programs including magnet schools and an international baccalaureate program. Learn more about what Gainesville has to offer at Visit Gainesville.
Expected Salary:
The salary is competitive and commensurate with qualifications and experience, and the compensation includes a full benefits package. To see more, visit, benefits.hr.ufl.ed.
Required Qualifications:

• A Ph.D. (by the start date) in Remote Sensing, Geography, Biology, Geospatial Science, Environmental Science, Ecology, or a closely related field.
• Demonstrated expertise in processing and analyzing remote sensing data (hyperspectral and/or Lidar is a strong plus).
• Strong proficiency in programming, particularly in Python and GEE for geospatial analysis and data science.
• Experience with machine learning/deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image or geospatial data.
• A track record of first-author publications in peer-reviewed journals.
• Excellent communication, collaboration, and writing skills.

Preferred:

• Experience in plant ecology, invasion science, or agronomy.
• Specific expertise in reflectance spectroscopy and chemometrics for vegetation analysis or high-throughput phenotyping.
• A strong background in GeoAI, computer vision, and data fusion techniques.
• Experience designing UAV-based remote sensing campaigns.
• Experience leading ground-based vegetation surveys.
• Demonstrated ability to work effectively in a collaborative, interdisciplinary research team.

Special Instructions to Applicants:
For full consideration, applications must be submitted online. Click on Apply Now at the top of this posting.
A complete application includes (1) a letter (max 2 pages) of application summarizing the applicant's qualifications, interests, and suitability for the position, (2) a complete curriculum vitae, (3) a statement on research goals, and (4) a list of three references. After initial review, letters of recommendation will be requested from the references for selected applicants.
Applications will be reviewed on a rolling basis starting immediately and will continue until the position is filled. The intended start date is flexible, ideally for the Spring 2026 semester. This is a full-time, 12-month appointment with the potential based on performance and funding availability.
Review of applications will be conducted on a rolling basis, with the first review beginning on November 15th.
All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.
The selected candidate will be required to provide an official transcript to the hiring department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.
Health Assessment Required:No
Advertised: 16 Oct 2025 Eastern Daylight Time
Applications close:
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