Postdoctoral Scholar - AI in Earth and Environmental Sciences

Job Description

The Department of Earth and Environmental Sciences at Syracuse University invites applications for a Postdoctoral Scholar position in the Hydrogeochemistry and Environmental Data Sciences (HANDS) research group. The position is broadly focused on artificial intelligence, machine learning, environmental data science, foundation AI models, and data-intensive Earth and environmental research.

The successful candidate will contribute to two complementary research directions. One direction uses AI/ML, data science, and geologic/environmental datasets to assess energy and environmental systems, including oil and gas well condition, characterization, and integrity-related questions. The second direction focuses on characterizing global water and elemental cycles, with emphasis on terrestrial and catchment systems. Together, these projects will use large geochemical, hydrologic, geospatial, regulatory, and environmental datasets to advance predictive, interpretable, and transferable approaches for Earth and environmental sciences.

A key intellectual theme of the position is the development and application of AI/ML and foundation-model approaches for complex Earth and environmental systems, including subsurface energy infrastructure, riverine hydrogeochemistry, watershed elemental cycles, water quality, terrestrial water and solute fluxes, and prediction across watershed and river-network scales.

Qualifications

• Ph.D. in geoscience, hydrology, geochemistry, environmental science, civil/environmental engineering, data science, computational geoscience, Earth system science, or a closely related field by the anticipated start date.
• Demonstrated experience in artificial intelligence, machine learning, environmental data science, statistical modeling, or related quantitative methods.
• Strong quantitative, programming, and data analysis skills.
• Ability to work with complex environmental, geospatial, hydrologic, geochemical, or Earth system datasets.
• Ability to develop reproducible computational workflows.
• Evidence of scientific communication through publications, presentations, reports, software, datasets, or related scholarly products.
• Ability to work both independently and collaboratively in an interdisciplinary research environment.

Job Specific Qualifications

Preferred qualifications include experience or interest in one or more of the following: AI/ML applications in energy and environmental systems; oil and gas well datasets; foundation AI models; application of AI/ML to catchment sciences; experience with large environmental datasets; scientific programming in Python or R; reproducible research tools.

Responsibilities

• Develop and apply AI/ML and environmental data science approaches to large datasets.
• Develop AI/ML-enabled workflows for energy and environmental systems.
• Investigate foundation AI models in catchment sciences.
• Integrate and analyze heterogeneous datasets.
• Build reproducible computational workflows.
• Prepare manuscripts and contribute to scholarly products.
• Mentor students.