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. These instruments and techniques support APS user programs and beamline scientists working in materials science, geology, and biology. The brain is among the most complex structures known, containing over 89 billion
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The Hydrogen and Fuel Cell Materials Group in Argonne National Laboratory’s Chemical Sciences and Engineering Division is seeking to hire a Postdoctoral Appointee to participate in a project that
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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS
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and no-carbon fuels for hard-to-electrify industrial equipment such as burners, furnaces, combined heat and power, etc., applications. The goal is to establish a world-class research program leveraging
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computer vision. Experience with multi-modal data fusion and alignment techniques. Experience with spatial transcriptomics or other -omics data analysis. Proficiency in Python programming and scientific
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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, in Electrical Engineering and Computer Science or related field obtained within the last five years. Experience with X-ray physics or optical wave modeling. Proficiency in programming with Python
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(electrochemistry, materials synthesis, or characterization) or computational simulations perspective, is required. Proficiency in Python programming is required. Familiarity with REST APIs is desirable. Master’s
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to develop and lead a world-class research program that strongly aligns with DOE priorities in low energy nuclear physics, as outlined in the 2023 Nuclear Science Advisory Committee Long Range Plan for Nuclear
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R