Postdoctoral Research Associate - Tokamak Transport Modeling

Requisition Id 11864 

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.

 

Oak Ridge National Laboratory has an exciting opportunity to develop novel machine learning capabilities for integrated modeling of fusion tokamak devices. The Power Exhaust and Particle Control (PE&PC) Group of the Fusion Energy Division aims to identify high performance plasma solutions that are compatible with the requirements for divertor control during long pulse operation, using synthetic edge diagnostics to combine simulation with experiment data analysis. The PE&PC group performs state-of-the-art simulations and collaborates with world-leading experiments on tokamak, stellarator, and linear plasma devices.

 

The selected candidate will apply plasma physics simulations of the tokamak core and pedestal using high performance computing resources and machine learning accelerated architecture. These simulations will inform integrated modeling for decision-ready tokamak pulse simulation to perform session planning of fusion experiments and simulated design of fusion reactors. Opportunities exist to participate in experiments at the DIII-D facility and to perform validation of physics code coupling. Machine learning techniques and statistical methods will be leveraged to build fast surrogate models that accelerate predictions of tokamak plasma scenarios.

 

Major Duties/Responsibilities: 

• Construct advanced machine learning models of core transport and pedestal properties for prediction of future tokamak experiments and comparison against other surrogate models trained on existing databases.
• Couple core transport, pedestal stability, and boundary plasma simulations using existing frameworks and contributing to the development of new integrated modeling methods,
• Collaborate with a broad and diverse team, including experimentalists, computational, and applied mathematics colleagues.
• Produce high impact publications in key peer-reviewed journals, and conference presentations on integrated modeling and machine learning for high performance tokamak plasmas.
• Ensure compliance with environment, safety, health, and quality program requirements.
• Maintain strong commitment to the implementation and perpetuation of ORNL’s values and ethics.
• 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:

• Have, or expect to have within 12 months a PhD in Plasma Physics, Electrical Engineering, Nuclear Engineering, Applied Mathematics, or a related field completed within the last 5 years.

 

Preferred Qualifications:

• Experience in plasma simulation using gyrokinetic, transport, integrated modeling, MHD, or boundary models.
• Experimental analysis of high-temperature plasmas.
• Experience in Bayesian inference and probabilistic models for data assimilation and adaptive sampling of parameter space.
• Excellent written and oral communication skills
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

 

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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

 

Please submit three letters of reference when applying to this position. You can 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.