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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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to substantially advance this new qubit platform by realizing high-fidelity two-qubit gates. The postdoc will design single electron qubit devices, fabricate them in CNM cleanroom, and characterize them in CNM
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photonic quantum devices for a heterogeneous quantum network, including but not limited to superconducting qubits, microwave-optical quantum transducers, etc. The postdocs will design the devices, fabricate
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The overarching focus of the postdoc position and effort is on advancing the understanding of materials at high pressure-temperature conditions, and in particularly across the solid-melt transition
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role of land–atmosphere interactions in S2S predictability; impacts on boundary layer processes, aerosol-cloud interactions, precipitation, and hydrological extremes, including feedback mechanisms
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interactions, or aerosol–cloud interactions Strong experience in numerical modeling and high-performance computing • Experience applying AI/ML methods to model development, with strong programming skills (e.g
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research prototypes to real-world deployment environments, including cloud, secure enclaves, trusted research environments, and leadership computing platforms. Candidates should be comfortable working in a
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The overarching focus of the postdoc position and effort is on advancing the understanding of materials at high pressure-temperature conditions, and in particularly across the solid-melt transition