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an independently-funded research program within 2-3 years. The successful candidate will develop and apply advanced data-driven methodologies to accelerate discovery in materials/chemistry design, characterization
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to formulate scientific problems relevant to nanoscale materials and DOE mission areas (e.g., microelectronics, energy capture/storage/conversion, quantum information science) Experience with data-intensive
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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications and
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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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
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Leadership Computing Facility (ALCF), the Mathematics and Computer Science Division (MCS), the Computational Science Division (CPS), and the Data Science and Learning Division (DSL). The postdoctoral
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computer-aided design software. Collaborative skills, including the ability to work well with other divisions, laboratories, and universities. Ability to demonstrate strong written and oral
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The Q-NEXT National Quantum Information Science and Research Center based at Argonne National Laboratory invites applications for a postdoctoral position to conduct research in the field
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator