Research Scientist, Geo-Physics Machine Learning (Hybrid Eligible)

Requisition Id15635

Overview:

We are seeking a Research Scientist who will support a growing portfolio of research in cutting edge physics-based machine learning, geophysical modeling, spatial and spatiotemporal methods. The candidate is expected to immediately contribute to uncertainty estimation in geophysical models and broader national security research initiatives. This position offers an exciting opportunity to leverage modern concepts of physics-informed machine learning, explainable AI, and for geophysical applications related to earth system modeling, geohazards, including but not limited to earthquakes, landslides, and volcanic activity. In addition to model development, research activities include the design of evaluation protocols that capture domain knowledge and sponsor application requirements.

Under the guidance of senior research scientists, the selected applicant will take roles on multidisciplinary teams supporting new research and engineering using ORNL's Frontier exascale supercomputer for its dense GPU-based HPC resources to deploy models and create large-scale production datasets for high-impact sponsor missions. The candidate will be expected to handle sponsor requirements and develop rapid prototypes to demonstrate new innovations. This position resides in the GeoAI Research Group in the Geographic Data Science Section, Geospatial Science and Human Security (GSHS) Division, National Security Sciences Directorate, at ORNL.

Major Duties/Responsibilities:

• Develop and implement physics-informed machine learning models for geophysical modeling, earth system modeling and geohazard prediction and assessment.
• Design algorithms integrating geophysical principles with explainable and interpretable AI techniques to enhance model interpretability and uncertainty quantification.
• Contribute to building visualizations and interfaces to communicate AI model decisions and uncertainties to diverse stakeholders.
• Contribute to research proposals, publish in high-impact journals, and present at international conferences.
• Collaborate with interdisciplinary teams to advance interpretable AI applications in geophysical and geoscience research.
• Ensure compliance with ORNL policies, standards, and procedures in all research activities.

Basic Qualifications:

• PhD in Geophysics, Earth Sciences, Computer Science, or a related field with a focus on computational geosciences.
• Two years of applied experience (professional or academic lab setting).
• Strong background in machine learning, artificial intelligence, and explainable AI techniques.
• Proficiency in scientific programming with experience in implementing interpretable ML models in Python and TensorFlow/PyTorch.
• Experience with geophysical data analysis, interpretation, and the application of AI/ML in geosciences and geophysics.
• Excellent written and verbal communication skills, with ability to explain complex AI concepts to diverse audiences.

Preferred Qualifications:

• Expertise in one or more geohazard-related fields (e.g., seismology, volcanology, landslide dynamics, earthquakes).
• Experience with physics-informed neural networks or other physics-based machine learning approaches.
• Knowledge of uncertainty quantification and interpretation in geophysical modeling.
• Familiarity with explainable AI techniques such as SHAP, LIME, or attention mechanisms in the context of scientific applications.
• Experience in developing interactive dashboards or visualizations for AI model interpretation.
• Track record of peer-reviewed publications in explainable AI, geophysics, and/or machine learning.
• Demonstrated ability to work in interdisciplinary teams and communicate AI insights to non-AI experts.

Special Requirements:

• Q or L clearance: This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.
• Visa Sponsorship: Visa sponsorship is not available for this position.

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain dedicated 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.

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.