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. Candidates should have demonstrated interest and expertise at the interface of high energy physics, dark matter phenomenology, condensed matter physics, and quantum information science. In addition to the core
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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-augmented AI tools Interfacing AI tools with experimental facilities at CNM and Argonne Key Responsibilities Research leadership (50%) Develop and lead an independent and collaborative research program in
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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-directed, collaborative research aligned with CNM’s strategic plan and for user support, including enabling workflows that couple computation, AI, and experimental measurement. Expertise in one or more of
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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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efforts in nanomaterials synthesis and in situ/operando characterization of liquid–solid interfaces during electrochemical conversions. This position offers the opportunity to leverage CNM’s advanced user
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., drag schemes, mesh resolution, feature representation); document improvements and limitations. Collaboration, mentoring, and dissemination. Collaborate with DOE E3SM, ICoM, and InteRFACE, projects as