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and simulation of the electronic structure of polycrystalline and defective two-dimensional materials. Interviews will begin immediately and continue until the position is filled. This position centers
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applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials
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needs. As a part of this team, you will : Develop, build and test equipment and perform molten salt separations which support the development of a secure fuel supply for MSRs and nuclear fuel cycle
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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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: - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics. - Experience with High-Performance Computing (HPC) systems and intelligent
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks a highly motivated postdoctoral researcher with deep expertise in electrochemistry. The successful candidate will lead
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Qualifications: Background in fracture mechanics-based reliability modeling. Familiarity with the basic structure-property relations for metallic and ceramic materials. Experience in engineering design
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This position will be dedicated to research projects aiming to unravel the fundamental interfacial processes in membrane and ionomer materials employed in energy conversion systems such as critical
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, both focused on multimodal synchrotron characterization of defects and interfaces in oxides and 2D materials. These positions are part of a cross-facility initiative to build an “AlphaFold
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to/from the memory via optical fibers. The candidate will be primarily responsible for: (1) advancing our experimental program to fabricate new hybrid devices in Argonne’s Center for Nanoscale Materials