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Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling. Density Functional Theory (DFT) for surfaces and
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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-based experiments, including accelerating gradient tests and breakdown studies of accelerating components. Collaborate with the APS/ASD mechanical engineering group on the fabrication of accelerator
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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. Experience with experimental physics and/or engineering is a plus. Presentation and documentation skills for describing research and clearly communicating results and data. Excellent collaboration skills and
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science, or a related engineering field is required. · To be eligible, candidates must have completed their Ph.D. within the last five years and must be available to start work by the end of 2025. Job
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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We seek a postdoctoral scientist with expertise in electrodeposition science and technology. Exposure to microelectronics applications is desirable, as is familiarity with progamming and interfacing
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing