Dr. Zhao’s lab in the UF/IFAS Agronomy Department at the University of Florida is seeking 1-2 highly creative and motivated PhD students in the areas of Geospatial Artificial Intelligence and Ecosystem Services. The successful candidates will conduct interdisciplinary research that integrates geospatial analysis with artificial intelligence to quantify and map Ecosystem Services across the continuum of urban and rural systems. Research topics include but are not limited to:
- Linking in-situ ground observations, GIS, remote sensing with AI methods (e.g., machine learning, deep learning such as convolutional neural networks) to quantify and map ecosystem service supply and demand in urban, grassland, rangelands, and other ecosystems.
- Examine effects of global change drivers (e.g., climate change, land use and land cover change, urbanization) and land management practices on the delivery of ecosystem services across landscapes.
- Investigate the interactions, tradeoffs and synergies among biodiversity and multiple ecosystem services across scales in varying socioeconomic and environmental conditions.
- Develop innovative web GIS and decision support tools related to ecosystem services, biodiversity, human health, and wellbeing to inform land use planning, natural resources management, and biodiversity conservation.
The candidate is expected to conduct independent research, author peer-reviewed publications, engage in outreach activities, and present research results at professional conferences. The successful candidate will work in a multidisciplinary environment among a team of faculty, postdoc, data analyst, and graduate students across a variety of fields, including Agronomy, Soil, Water and Ecosystem Sciences, Geography, Ecology, Electrical and Computer Engineering. The position offers a competitive stipend, a tuition waiver, and subsidized health insurance.
Start date: Spring 2024 or Fall 2024
Organization: University of Florida
Location: Gainesville, Florida, USA
Email Address: [email protected]
Required Qualifications:
- A bachelor or master’s degree in Geography, Geographic Information Science, Geoinformatics, Environmental Science, Ecology, Statistics, Computer Science, or related fields.
- Backgrounds in geospatial data science and statistical methods.
- Strong interest in machine learning and deep learning.
- Proficiency with one or more scientific programming languages (e.g., Python, R).
- Excellent written and oral communication skills in English.
- Strong motivation, work ethics and the ability to work independently.
Desired Skills:
- Proficiency with GIS programming and Earth Observation data processing tools, e.g., Google Earth Engine, ArcGIS Pro, Web GIS development with R Shiny, ArcGIS Online, ArcPy, ArcGIS API for Python, QGIS, ENVI and ERDAS.
- Familiar with deep learning library, e.g., PyTorch, Tensorflow, Keras.
- Research experience in remote sensing data processing, e.g., RGB and multispectral satellite and aerial images, LiDAR point clouds and hyperspectral images.
Candidates with prior research or work experience with ecosystem service assessments or machine learning and deep learning for interdisciplinary ecology studies are strongly encouraged to apply.
Application:
If you are interested, please email Dr. Chang Zhao ([email protected]) with all materials in a single PDF document that includes:
- Your most recent CV
- Unofficial undergraduate and graduate transcripts
- A short (1-2 page) research statement about your skills and experience in geospatial artificial intelligence and ecosystem service assessments, your career goals, and how you will connect existing experiences and skillsets with future research plans. Please also indicate where you heard about this job opportunity.
- Contact information of three references.
Applications will be reviewed continuously as they arrive. Shortlisted candidates will be contacted and interviewed virtually in a timely manner.
About Us:
The PhD student will join the Geospatial Artificial Intelligence and Ecosystem Services lab led by Dr. Chang Zhao. Dr. Zhao is an assistant professor in the Agronomy Department, UF/IFAS, and leads an interdisciplinary research team affiliated with the Department of Geography, School of Natural Resources and Environment, and Global Food Systems Institute. Our students and staff are encouraged to pursue multidisciplinary coursework and engage with diverse interdisciplinary experts in social, environmental, and economic disciplines. The School of Natural Resources and Environment offers nationally and internationally recognized Ph.D. programs in Interdisciplinary Ecology, and the Agronomy Department offers Ph.D. programs in Ecology and Statistical Methods Specialization.