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Assistant position. This role focuses on advancing cutting-edge power electronic systems and their integration into the modern electric grid. You will develop innovative power electronic converters and
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analysis of novel geothermal energy systems and components in various applications. The work will involve developing experimental setups, problem-solving, conducting experimental campaigns, performing
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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analyses, and analysis techniques. Knowledge of software platforms, such as VISO and SolidWorks, to prepare process flow sheets, analyze process data, and prepare reports. Ability to function well in a fast
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have been incorporated in the processes. Lead and support operational performance assessments as needed. Perform data analysis for process improvement initiatives. Utilize a variety of lean process
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Directorate. In this role, you will lead the development and application of physics-informed data science and machine learning approaches to support nuclear nonproliferation missions. The successful candidate
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and characterization: Python security automation; working knowledge of Assembly, C/C++, and Java. Binary literacy with static/dynamic analysis; reverse engineering familiarity (Ghidra, IDA) and fuzzing
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. The Advanced Engineering Technologies Group focuses on developing innovative approaches for the operation, characterization, and analysis of nuclear fuel cycle processes. The group applies engineering principles
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, conference papers, and peer-reviewed journals. Work with industrial, university, and/or laboratory partners on multi-disciplinary projects and teams. Oversee fabrication and testing of developmental systems
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innovation, and materials research capability expansion. This position resides in the Radiation Effects and Microstructural Analysis Group (REMAG) within the Materials in Extremes Section, Materials Science