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interact within their natural environments. Your Role This position focuses on developing learning-enabled imaging methods to guide data collection and analyze synchrotron datasets, spanning the full
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and interpret experimental data and share research findings through scientific conferences and peer-reviewed publications. Key Responsibilities Conduct research on the distribution and behavior
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energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization. This position offers the opportunity to work with a multidisciplinary team of
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, electrical characterization, and electrochemical measurements. Perform interfacial characterization to understand bonding mechanisms between nanomaterials and matrix phases. Analyze experimental data, develop
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time The expected hiring range for this position is $72,879.00-$121,465.00. Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be
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candidate will develop a novel multiscale multimodal experimental apparatus with precise control during data acquisition, as well as work on data processing pipeline, adaptable to imaging of energy-conversion
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nonlinear MEMS-based oscillators driven by storage-ring radio-frequency (RF) signals to enable advanced manipulation of X-ray pulses. Background information on the project can be found in the publications
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processes Implement models and perform numerical simulations Analyze and interpret simulation and experimental data Integrate AI tools and workflows to enhance modeling and accelerate learning Collaborate
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facilities. Perform thermochemical and thermophysical properties measurements of MSR relevant molten salts to understand the impact of evolving salt composition on property values and provide this data
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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user