The goal of this project is to develop foundation models that significantly reduce the cost of design exploration for energy flow systems, including fission and fusion nuclear reactors. The project integrates high-fidelity simulation data generated using the high-order spectral element code Nek5000/RS with machine learning methodologies to enable automated design workflows. Demonstrations will focus on the design and optimization of critical thermal-fluid components relevant to advanced energy systems. Education and Experience Requirements The entirety of the appointment must be conducted within the United States. Applicants must be: o Currently enrolled in undergraduate or graduate studies at an accredited institution. o Graduated from an accredited institution within the past 3 months; or o Actively enrolled in a graduate program at an accredited institution. Must be 18 years or older at the time the appointment begins. Must possess a cumulative GPA of 3.0 on a 4.0 scale. If accepting an offer, candidates may be required to complete pre-employment drug testing based on appointment length. All students remain subject to applicable drug testing policies. Must complete a satisfactory background check.
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Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees