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networking, distributed quantum computing, quantum-system architectures, or closely related areas. Develop models, algorithms, simulation capabilities, and research software for the design and evaluation
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device-relevant properties Design active learning, Bayesian optimization, uncertainty-aware modeling, and other adaptive experimental design workflows to guide experiments and improve data efficiency in
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solid electrolytes. We are seeking candidates who will be able to design experiments and develop methodologies to design material compositions, ink rheological properties, and coating and drying process
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together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
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High Energy Physics Division, the successful candidate will contribute to the design, fabrication, and characterization of superconducting devices based on microstrip-coupled TES technology, with
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. As part of a multidisciplinary team spanning multiple Argonne divisions, you will contribute to the design, fabrication, and characterization of superconducting devices based on high kinetic inductance
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Responsibilities : Spearhead the research and development of predictive models and strategic tools designed to support decision making in strengthening both domestic and international supply chains, particularly
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The Applied Materials Division at Argonne National Laboratory has an immediate opening for a Postdoctoral Appointee. The candidate will be responsible for reviewing and developing design methods and
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, for on-chip magnon quantum sensing Position Requirements Superconducting resonator design, simulation and nanofabrication. Microwave circuit design and characterization, including vector network analyzer
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strongly recommended but not required. The candidate will design or modify laboratory procedures and protocols, develop experimental designs, run technical experiments, make detailed observations, gather and