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CHEManager International · 1 day ago

Postdoctoral Research Associate - AI for Hydrological Modeling

Oak Ridge, TN

Full-time

Onsite

New Grad, Entry Level

CHEManager International is seeking a highly motivated Postdoctoral Research Associate in the areas of Hydrological and Earth System Modeling and Artificial Intelligence at Oak Ridge National Laboratory (ORNL). The successful candidate will develop and apply AI foundation models for hydrological modeling, collaborate with a multidisciplinary team, and contribute to the advancement of predictive understanding of complex environmental systems.

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Responsibilities

Develop and apply AI foundation models for hydrological and Earth system modeling, with emphasis on improving predictive capabilities for compound flooding in coastal regions

Design and implement physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction

Conduct multimodal, multiscale data analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation

Collaborate with a multidisciplinary team of hydrologists, Earth scientists, and computational scientists to leverage leadership-class computing resources for large-scale model training, testing, and deployment

Contribute to the development of scalable, explainable, and uncertainty-aware AI methods that enhance model robustness, reliability, and scientific discovery

Publish research findings in high-impact journals and present results at national and international conferences

Engage with collaborators across DOE laboratories, universities, and partner agencies to broaden the applications of AI-enabled hydrological modeling

Ensure compliance with ORNL's safety, security, quality, and environmental standards while carrying out all research activities

Qualification

Hydrological modelingEarth system modelingAI/ML techniquesComputational sciencesScientific programmingHigh-performance computingScholarly productivityCommunicationCollaborative teamwork

Required

A Ph.D. in Hydrology, Earth system science, Water resources engineering, Computational sciences, Computer sciences or a related field completed within the last 5 years (or expected soon)

Demonstrated experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction

Strong background in computational sciences, including numerical methods, high-performance computing (HPC), or large-scale data analysis

Experience in applying AI/ML techniques to hydrological and Earth sciences

Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C++

Evidence of scholarly productivity, including peer-reviewed publications and conference presentations

Excellent written and oral communication skills and the ability to work effectively in a collaborative, multidisciplinary team environment

Preferred

Knowledge of uncertainty quantification methods and causal inference for complex environmental systems

Experience with large-scale Earth system simulations, particularly using the Energy Exascale Earth System Model (E3SM)

Background in coastal and compound flooding simulations, including subsurface-surface and hydrodynamic interactions

Demonstrated ability and strong motivation to conduct innovative, high-impact research and disseminate results through peer-reviewed publications and conference presentations