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Develop and apply operando diagnostic tools for aqueous battery research Design, perform, and analyze electrochemical and materials characterization experiments Use imaging and sensing techniques, including
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) at Argonne National Laboratory to advance learning-enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied
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across heterogeneous data types such as clinical, imaging, omics, text, and experimental data. The work will include developing approaches for continual model improvement, adaptive federated training
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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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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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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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(HPC). The postdoc will work closely with visualization researchers, AI scientists, and domain application teams across Argonne and the broader DOE ecosystem. The goal of this postdoctoral position is to