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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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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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camera technology and multiplexed readout systems for quantum information science applications. In this role, you will join a multidisciplinary team spanning several Argonne divisions and contribute
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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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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
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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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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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal