Research Scientist - Computational Hydrology

Requisition Id: 13189

Overview

The Computational Hydrology and Atmospheric Sciences Group (CHAS) within the Computational Sciences and Engineering Division at Oak Ridge National Laboratory (ORNL), is actively seeking a scientist. This role is aimed at advancing hydrologic modeling and Earth system predictability by developing and applying Computational and Artificial Intelligence (AI)/Machine Learning (ML) methods. The successful candidate will bring strong expertise in computational sciences, hydrologic sciences, data analytics, high-performance computing (HPC), and Earth sciences. Our CHAS group excels in world-class research in hydrologic and atmospheric system modeling, large-scale data analytics, ML, and model-data integration at the US Department of Energy (DOE’s) Leadership Class Computing Facilities (LCFs).

As a premier national laboratory under the U.S. Department of Energy (DOE) Office of Science, ORNL boasts an illustrious 80-year history dedicated to solving the nation’s most challenging problems. With over 6,000 dedicated staff, our commitment to diversity, equity, inclusion, and accessibility (DEIA) aims to foster a nurturing environment that promotes a varied spectrum of ideas and people. This is central to ORNL’s mission to accelerate scientific discoveries into actionable energy, environment, and security solutions for the nation.

Major Duties/Responsibilities

• Collaborate with Earth scientists to enhance hydrologic, atmospheric, and Earth system modeling.
• Develop and implement scalable computational and AI/ML methods for improving hydrologic and Earth system model prediction, uncertainty quantification (UQ), and data assimilation.
• Integrate multimodal data with multi-type models on diverse HPC platforms.
• Work with a diverse team of Earth system and computational scientists within the CHAS group, DOE Labs, and partner universities to leverage model-data integration for improving Earth system predictability.
• Publish research in leading peer-reviewed journals and present findings at national and international conferences.
• Uphold ORNL’s core values of Impact, Integrity, Teamwork, Safety, and Service. Foster diversity, equity, inclusion, and accessibility by nurturing a respectful workplace, collaborative interactions, and measuring success.

Basic Qualifications

• 2 years of post-Ph.D. experience.
• Ph.D. in a relevant discipline to Computational Hydrology.
• A history of high-quality publications in peer-reviewed, international journals.

Preferred Qualifications

• Experience in multiscale numerical simulation and ML-physics hybrid modeling of complex hydrologic and Earth systems.
• Expertise in assurance for AI, including UQ and AI/ML system explainability.
• Proficiency with Linux, LaTeX, Git, Python, Fortran, C/C++, OpenMP/MPI, and GIS software.
• Background in software development, especially in compute codes for data analysis and AI/ML algorithms.
• Skill in computational scalability and AI/ML algorithm performance, particularly in HPC systems like Frontier at ORNL.
• Ability to collaborate with a diverse range of scientists, engineers, and students.
• Experience in various Earth science AI/ML applications.
• Experience in proposal writing.
• Strong interpersonal skills, exceptional communication abilities, organization, and personal motivation.

Technical Questions

For technical inquiries, please contact Dan Lu at .

Benefits at ORNL

ORNL offers competitive compensation and benefits to attract and retain top talent. Our comprehensive employee benefits include medical and retirement plans, flexible work hours, and on-site fitness, banking, and cafeteria facilities. Our other benefits include:

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits