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-world problems. Position Requirements Recent or soon-to-be completed (typically within the last 0-5 years) PhD in Electrical Engineering, Industrial Engineering, Applied Mathematics, or a closely related
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The Nanoscience and Technology Division (NST) at Argonne National Laboratory invites applications for a postdoctoral researcher to lead cutting-edge efforts in electrically driven ultrafast electron
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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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the last 0-5 years) in the field of electrical engineering, experimental physics, materials science, and mechanical engineering, or related discipline Experience in electron beam lithography and/or micro
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it in Physics with a focus on accelerator physics, or Electrical Engineering with a focus on RF/Accelerator Physics Strong background in accelerator physics and beam diagnostics. Excellent problem
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optimization of hydropower systems and their integration with broader electricity markets. Conduct research on electricity system operations, planning, and market design, including evaluation of economic and
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avenues will be pursued: advancing our toroidal anvil capabilities to extend the maximum achievable pressure ranges; and depositing designed electrical circuits to create advanced multi-modal experiments
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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The Vehicle Technology Assessment (VTA) Group within the Vehicle and Mobility Systems at Argonne National Laboratory is seeking to hire a postdoctoral appointee to assess vehicle technologies
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for critical energy and technology sectors. Ability to assess the economic and operational impacts of large-scale AI adoption (e.g., data centers, compute infrastructure) on U.S. electricity demand, generation