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, energy storage and conversion materials, correlated electron systems, and AI/ML-accelerated materials discovery. • Lead the development of ambitious, cohesive research agendas that leverage MSD’s core
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catalysis focused on the discovery of new catalytic materials and processes. Materials development will focus on elucidating the chemical and physical properties (physical, structural, thermodynamic, etc
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that values scientific rigor, collaboration, and professional development. Position Requirements Required Qualifications RD3: Ph.D. in computer science, electrical or computer engineering, physics
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In the Computational Materials Group, we focus on the development and use of computational and theoretical methods to understand and predict the behavior of solids, liquids, and nanostructures from
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development, and mentor postdoctoral researchers, graduate students, and visiting scientists. Candidates must hold a Ph.D. in physics, materials science, chemistry, or a closely related discipline and possess
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nanofabrication. Areas of interest include, but are not limited to, the development of energy-efficient electronic systems through heterointegration for applications in RF electronics, power electronics, and
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Development & Support: Lead the enhancement, modernization, and troubleshooting of control systems for 60+ insertion devices and associated infrastructure, primarily using the EPICS framework. Operations & AI
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catalyst design. This role involves conducting multiscale modeling, spectroscopy simulations, and the development of machine learning methods and automated workflows for multi-fidelity, multiscale, and
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synthesis, characterization, beamline science, theory, and computing Contribute to the development of scalable computational and data workflows spanning edge, beamline, and HPC environments Publish in peer
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(APS). The GL also contributes to the development of next-generation microscopy methods, instrumentation, and data workflows, while overseeing the group’s day-to-day operations, budget, user science