Oak Ridge National Laboratory
Just Landed
Posted Yesterday
Postdoctoral Research Associate in AI/ML for Gulf Coast Ecosystem Dynamics Oak Ridge National Laboratory in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Postdoctoral appointment up to 24 months with potential extension, subject to performance and availability of funding. ORNL offers competitive pay and benefits, including medical, retirement, relocation assistance, and other employee benefits.
Country
United States
University
Oak Ridge National Laboratory
How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
About this position
Oak Ridge National Laboratory (ORNL) is recruiting a Postdoctoral Research Associate for the Computational Hydrology and Atmospheric Science (CHAS) Group in the Computational Sciences and Engineering Division. The position supports the Exploring Gulf Region Ecosystem Transitions (EGRET) project, an interdisciplinary effort focused on disturbance-driven ecosystem transitions across the United States Gulf Coast.
The research centers on artificial intelligence and machine learning, remote sensing, Earth and environmental sciences, hydrology, geospatial analysis, and time-series datasets. The successful candidate will develop multimodal AI models to characterize vegetation and land-surface dynamics, quantify ecosystem responses and recovery after hurricanes and other disturbances, and help build reproducible AI-ready datasets and workflows.
Key scientific themes include coastal ecosystem resilience, plant–microbial–soil interactions, inundation and salinity gradients, explainable AI, and large-scale environmental data integration. The role involves collaboration with scientists across DOE laboratories and universities, plus publication of results in peer-reviewed journals and presentation at conferences.
Eligibility highlights: Ph.D. in Earth and Environmental Sciences, Hydrology, Computational Sciences, Remote Sensing, Data Science, or a related field; degree completed within the last 5 years or expected soon; experience with AI/ML for Earth or environmental problems; programming in Python, GEE, or R; and experience with large heterogeneous geospatial or remote-sensing datasets. Preferred experience includes transformers, multimodal learning, representation learning, satellite products such as Landsat, Sentinel, MODIS, SAR, or LiDAR, and geospatial foundation models.
Funding and appointment: This is a postdoctoral appointment for up to 24 months with possible extension, depending on performance and funding availability. ORNL provides competitive pay and benefits, including medical, retirement, relocation assistance, and other employee benefits.
How to apply: Apply through the ORNL jobs portal using the provided application link. Submit the required application materials and three letters of reference. For technical or project questions, contact the listed ORNL researchers by email.
Funding details
Postdoctoral appointment up to 24 months with potential extension, subject to performance and availability of funding. ORNL offers competitive pay and benefits, including medical, retirement, relocation assistance, and other employee benefits.
What's required
A Ph.D. in Earth and Environmental Sciences, Hydrology, Computational Sciences, Remote Sensing, Data Science, or a related field, completed within the last 5 years or expected soon. Applicants should have demonstrated experience applying AI/ML to Earth, environmental, ecological, hydrological, or geospatial problems, programming experience in Python, GEE, or R, and experience analyzing large heterogeneous environmental, geospatial, remote-sensing, or time-series datasets. A strong publication or conference record and excellent written and oral communication skills are required. Preferred experience includes transformers, multimodal learning, representation learning, satellite remote sensing (Landsat, Sentinel, MODIS, SAR, LiDAR), geospatial foundation models, explainable AI, and interdisciplinary coastal or wetland ecology research.
How to apply
Apply through the ORNL jobs portal using the View or Apply link. Submit your application materials and three letters of reference. If needed, upload documents in your candidate profile under My Documents.
More information can be found here
Ask ApplyKite AI
How do I apply for this?
Sign in for free to reveal details, requirements, and source links.