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of the microstructural evolution and its relationship to mechanical behavior in steels, magnesium, aluminum, and Ni-based alloys. This knowledge will be used to evaluate the suitability of these alloys in automotive
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of researchers, technical professionals, and software developers focused on conducting research in world-class facilities and deploying science-based knowledge in real-world applications. The position supports
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Laboratory (ORNL). This position will focus on the application of your knowledge to the chemistry of advanced nuclear fuel cycles. In this position, you will develop processes that convert products and
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in ORNL’s Center for Radiation Protection Knowledge (CRPK). The candidate will work with experts in computational radiation dosimetry and risk assessment. The candidate should be an independent thinker
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-microbe interaction studies Experience in plant stress physiology and phenotyping Proficiency in molecular biology techniques Experience analyzing and interpreting multi-omics datasets Knowledge of plant
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for low- and medium- energy beams in the SNS and test stand experiment. Conduct studies to reveal and resolve sources of discrepancy between simulation and measurement. Apply knowledge gained through test
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), to study nano-sized features in bulk materials at MARS (https://neutrons.ornl.gov/mars ). By participating and contributing to this project, you will gain experience and knowledge in neutron imaging
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for low- and medium- energy beams in the SNS and test stand experiment. Conduct studies to reveal and resolve sources of discrepancy between simulation and measurement. Apply knowledge gained through test
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record. Self-motivated. Preferred Qualifications: Familiarity with U.S. natural gas energy infrastructure and grid operations. Experience working with government or utility partners. Knowledge thermal
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generative design tools such as HEEDS, and/or the Dakota or RAVEN uncertainty quantification tools. Experience with FORTRAN, C, and/or C++ applied programming. Knowledge of Python, Java, or other scripting