Requisition Id 14736
Overview:
The Workflow Systems Group in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a staff fellow with expertise in machine learning and high performance computing to help develop high-fidelity computational tools that are used for large-scale, physics-based simulations of fusion energy systems in partnership with the University of Tennessee-Oak Ridge Innovation Institute (UT-ORII). As part of the UT-ORII Convergent Research Initiative on Accelerating Fusion Technology and as an ORNL UT-ORII staff fellow, successful applicants will be part of a team of Research Faculty and ORNL staff to collaborate in the area of Fusion Materials.
In this role, you will work with groups of scientists across ORNL and the University of Tennessee (UT) to develop and apply physics-informed AI surrogate models for scientific simulations to accelerate research in fusion energy systems. This includes developing new machine learning models and software for scale-bridging and physics coupling in multiscale and multiphysics simulation codes for materials science and plasma-material interactions in fusion energy systems. You will also advance knowledge of key AI methods such as deep learning, operator learning, and Bayesian optimization, and apply it to develop next-generation surrogate models. This position will enable you to coordinate and conduct research and experiments related to the performance and reliability of AI surrogate models as well as develop mechanistic understanding and models for relations among simulation parameters, AI models, and predictive performance.
As a UT-ORII fellow, your career will develop in collaboration with researchers from both UT and ORNL through this early-career position primarily located at ORNL and with a Joint-Research Faculty (JFO) appointment at UT. As an integral part of the team, you will engage in a dynamic blend of activities, from advanced AI model developments and AI deployments to accelerate fusion material development to crafting comprehensive reports and impactful proposals. In addition to helping shape research programs, mentorship will be a key aspect of your role, guiding and inspiring graduate and undergraduate students. As a valued, emerging researcher in the ORNL Computing and Computational Sciences Directorate and the UT-OR Innovation Institute, you'll have access to a rich network of resources, including seminars, training opportunities, and collaborations that will propel your career forward.
UT-ORII was founded in 2019 by the University of Tennessee and Oak Ridge National Laboratory to help the US maintain prominence as a global leader in innovation and discovery, and to create a robust talent pipeline in areas of growing national need and demand. UT-ORII is funded by the Department of Energy and the State of Tennessee.
More About the Workflow Systems Group:
The Workflow Systems Group researches and develops systems and algorithms to enable knowledge discovery from scientific data through efficient data management, reduction, and analysis. The group's goal is to accelerate scientific knowledge by researching and developing novel techniques capable of solving real-world problems for mission critical applications and exploring novel solutions in the research community. The ability to create next-generation workflows for in situ processing and federated scientific instruments is a central component of this approach.
More About UT-ORII:
The University of Tennessee-Oak Ridge Innovation Institute is a partnership of Oak Ridge National Laboratory (ORNL) and UT created to prepare interdisciplinary leaders in energy, science, and technology and develop a world-class workforce for industry, government, and academia that will drive innovation and create the industries of the future. More information is available at University of Tennessee - Oak Ridge Innovation Institute (utorii.com). Today’s energy economy is driven by disruptive technologies and swift change. The US is in a global competition for jobs, talent, and investment. To successfully compete, we must develop leadership talent in research and development (R&D), encourage entrepreneurship, and create an educational environment that promotes rapid innovation and attracts skilled professionals. Leveraging a 75-plus-year UT-ORNL partnership, UT and ORNL have developed joint institutes, joint facilities, interdisciplinary PhD programs, and comprehensive joint faculty arrangements, including 17 Governor’s Chairs recruited for the significance of their impacts in their fields. UT-ORII’s overall goal is to become a center for convergent research and talent development, helping maintain US prominence as a global innovation leader and providing tangible benefits to Tennessee.
More About Oak Ridge National Laboratory:
Since its establishment in 1943, Oak Ridge National Laboratory (ORNL) has been delivering scientific discoveries and technical breakthroughs needed to realize solutions in energy and national security and provide economic benefit to the nation. More than 7,000 employees representing 60+ nations apply unique facilities, sophisticated tools, and signature strengths in neutron science, high-performance computing, advanced materials, biology and environmental science, clean energy, fission and fusion science and engineering, isotopes, and national security research to benefit science and society. In addition, ORNL’s wide range of partnerships with other US Department of Energy (DOE) laboratories and programs, universities, and industry have enabled outstanding contributions to science. Over the years, ORNL researchers have received Nobel Prizes, contributed to the discovery of elements, received hundreds of R&D 100 Awards, and more.
Responsibilities include, but are not limited to:
- Develop and apply physics-informed AI surrogate models for scientific simulations to accelerate the research in fusion energy systems.
- Advance knowledge of key AI methods such as deep learning, operator learning, and Bayesian optimization, and apply it to develop next-generation surrogate models.
- Coordinate and conduct research and experiments related to the performance and reliability of AI surrogate models.
- Develop mechanistic understanding and models for relations among simulation parameters, AI models, and predictive performance.
- Communicate and coordinate experimental results with other domain experts to facilitate collaborations.
- Present and report research results and publish scientific results in peer-reviewed journals in a timely manner.
- Ensure compliance with environment, safety, health, and quality program requirements.
- Maintain strong dedication to the implementation and perpetuation of values and ethics.
Basic Qualifications:
- A PhD in Computer Science, Applied Mathematics, Computational Science, Materials Science, Nuclear Engineering, or a related discipline.
- Demonstrated research experience with AI and machine learning techniques, particularly in scientific applications.
- Demonstrated hands-on experience and understanding of developing and applying AI-based surrogate models.
- Excellent written and oral communication skills and the ability to communicate in English to an international scientific audience.
Preferred Qualifications:
- Knowledge of high-performance computing and its application to AI model training and deployment.
- Knowledge of surrogate modeling techniques and their application in scientific research.
- Knowledge of design and analysis of complex systems using AI.
- Knowledge of data management, high performance I/O, and data compression methods.
- Experience working in a cross-discipline team with other modelers and experimentalists.
- An excellent record of productive and creative research as demonstrated by publications in peer-reviewed journals.
- Motivated self-starter with the ability to work independently and to participate creatively in collaborative and frequently interacting teams of researchers.
- Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever-changing needs.
Special Requirements:
Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to ORNLRecruiting@ornl.gov (For postdocs, use 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
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.
ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added 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.
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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.
