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Argonne National Laboratory’s Materials Science Division (MSD) invites applications for a Postdoctoral Appointee in computational materials chemistry and atomistic modeling to investigate
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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to conduct computational research focused on transition metal-containing clusters
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The Data Science Learning division is seeking a postdoctoral researcher to develop and apply artificial intelligence and computational biology methods to investigate the molecular and cellular
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potential impact across quantum networking, communications, and computing. Research Focus Design and fabricate superconducting devices that leverage the nonlinear kinetic inductance of thin superconducting
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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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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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, or network-based modeling of infrastructure or industrial systems. Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization
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characterization, and machine learning. The role offers the opportunity to leverage Argonne’s world-class scientific capabilities and engage with a strong network of internal and industry collaborators. Position
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successful candidate will collaborate with scientists in DIS, Environmental Sciences division and Argonne leadership Computing Facility to further develop the AI foundation models, benchmarking and deploy them