Postdoctoral Research Associate - Computational Hydrology

Requisition Id 13647 

­­Overview:  

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

The Computational Hydrology and Atmospheric Science Group (CHAS) at the Oak Ridge National Laboratory (ORNL) is seeking a qualified postdoctoral candidate in the fields of Hydrological and Earth System Modeling and Artificial Intelligence (AI) with a strong background in computational sciences, statistics, hydrological modeling, and Earth system modeling. ORNL’s CHAS group conducts world-class research and development in hydrological and Earth system modeling, large scale data analytics and machine learning (ML), and model-data integration at the US Department of Energy’s (DOE’s) Leadership Class Computing Facilities (LCFs).

Major Duties/Responsibilities:

• Work with the AI research team to develop ML and data analytics algorithms, including physics-informed AI, explainable AI, causal AI, and uncertainty quantification (UQ) methods for advancing hydrological and Earth system modeling.
• Develop computational scalability and performance of ML algorithms and large-scale hydrological and Earth system models, including the scaling of algorithms and simulation models and HPC implementations.
• Analyze multi-scale, multi-modal data, including model simulation data, in-situ observation data, and remote sensing data, and extract information from the data to inform model development.
• Collaborate with a diverse team of hydrologist, Earth scientists, and computational scientists, both within the CHAS and across DOE Labs and partner universities, to apply AI/ML algorithms aimed at enhancing predictive understanding of the Earth system.
• Develop physics-informed ML algorithms, including effective and realistic surrogate modeling and physics-data-integrated hybrid modeling.
• Publish research in peer-reviewed journals and present results at national and international conferences.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• A Ph.D. in water resources, hydrology, earth system science or computational sciences or a related field completed within the last five years.
• Research experience in AI/ML and hydrological modeling.
• Experience in data analytics.

Preferred Qualifications:

• Knowledge of data analytics, UQ, causal inference, and AI/ML algorithms.
• Experience with simulations using the Energy Exascale Earth System Model (E3SM).
• Experience with coastal compound flooding simulation.
• Experience with the Linux operating system, LaTeX, Git, Python, and Fortran.
• Collaborative research capabilities as demonstrated by existing peer reviewed publications and technical proposals.
• Strongly motivated to perform and publish leading edge research.
• Excellent verbal and written communication skills.

Technical Questions:

Please contact Dan Lu lud1@ornl.gov

ORNL Ethics and Conduct:

As a member of the ORNL scientific community, you will be expected to commit to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here:  https://www.ornl.gov/content/research-integrity

Special Requirements:

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

Benefits at ORNL:   

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience. 

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. 

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.