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methods that aim to transform scientific discovery and leverage high-performance computing. Specifically, this will include research in : 1. Developing large-scale agent-based and other complex systems
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(LOHCs) Perform detailed studies to understand reaction mechanisms, determine reaction kinetics, and measure the heat of adsorption of LOHCs in porous materials Collaborate with multidisciplinary teams
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mechanisms through reaction kinetics analysis and other physical organic and inorganic techniques Perform detailed in situ / operando studies of catalysts using X-ray Absorption and Emission Spectroscopies
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Investigate how dynamic stimuli manipulate catalyst electronic properties, and how these stimuli can manipulate catalytic elementary steps and reaction outcomes Perform detailed in situ / operando studies
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-based high-resolution surface-sensitive methods. In addition, working with the APS staff scientists, the successful candidate will demonstrate the applications to probe surface and interface nanomaterials
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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for next-generation high-voltage, high-energy electrochemical energy storage intended for electric vehicle applications. The project focuses on the design and synthesis of novel electrolyte materials
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seeking a postdoctoral appointee to join our team focused on designing the communication infrastructure for next-generation High-Performance Computing (HPC) and Artificial Intelligence (AI) systems
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dynamics (CFD) to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical