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<b>Postdoctoral Research Associate: GeoAI and Remote Sensing for Invasive Species Ecology</b></div>
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<b><u>Job Description</u></b>: 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 provides a professional development opportunity to grow collaborations with partners at academic institutions, government agencies and private and non-profit sectors in Montana and Idaho. The successful
candidate will lead the development and implementation of cutting-edge remote sensing and machine learning techniques to address critical questions about VEDU surveillance and invasion dynamics. Key research themes include: 1) characterizing VEDU 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. </div>
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<b><u>Responsibilities</u></b>: · Design and lead coupled field and 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 VEDU invasion 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 preparation of high-impact, peer-reviewed publications. · Present research findings at national and international scientific conferences. ·
Mentor graduate and undergraduate students 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 6th in the country among
public universities (US News and World Report 2023 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.</div>
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<b><u>Salary</u></b>: 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.edu.</div>
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<b><u>Minimum Requirements</u></b>: · 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.</div>
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<b><u>Preferred Qualifications</u></b>: · 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.</div>
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<b><u>Special Instructions to Applicants</u></b>: For full consideration, applications must be submitted online. 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. 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/. The University of Florida is committed to promoting an environment that welcomes all abilities, classes, ethnicities/races,
gender identities and expressions. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service.</div>
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<span style="letter-spacing: -0.133333px; font-family: "Arial Narrow", sans-serif; font-size: 14pt; color: rgb(111, 38, 61); background-color: white;"><b><i>Jessica J. Mitchell</i></b></span></p>
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<span style="letter-spacing: -0.133333px; font-family: "Arial Narrow", sans-serif; font-size: 10pt; color: rgb(111, 38, 61);"><b><i>DIRECTOR</i></b></span></p>
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<span style="font-family: Arial, sans-serif; font-size: 8pt; color: rgb(111, 38, 61);"><b><a style="margin: 0px;" rel="noopener noreferrer" title="https://www.umt.edu/spatial-analysis-lab/" class="OWAAutoLink" id="OWA5f4c83b5-ee75-234d-248e-97a423747e47" target="_blank" href="https://www.umt.edu/spatial-analysis-lab/">Spatial
Analysis Lab </a></b></span></p>
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<span style="font-family: Arial, sans-serif; font-size: 8pt; color: rgb(111, 38, 61);"><b>NS 313 | 32 Campus Drive | 406-544-9256</b></span></p>
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<span style="font-family: Arial, sans-serif; font-size: 8pt; color: rgb(111, 38, 61);"><b>jessica.mitchell@mso.umt.edu</b></span></p>
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<span style="letter-spacing: 1.55pt; font-family: "Arial Narrow", sans-serif; font-size: 9pt; color: rgb(111, 38, 61);"><i>UNIVERSITY OF MONTANA</i></span><span style="font-family: "Minion Pro", serif; font-size: 9pt; color: rgb(111, 38, 61);"> </span></p>
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