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on ab initio data to accurately model the thermodynamic and thermophysical properties of complex materials. Conduct molecular simulations to elucidate the thermodynamic and structural basis of enhanced
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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objectives. Basic Qualifications: A Ph.D. in materials science, physics, chemistry, nuclear engineering, or related disciplines. Preferred Qualifications: Experience with ellipsometry Experience with data
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maturation, characterizing performance and properties of nuclear fuels and materials, and generate the data to advance physical modeling and simulation. The primary function of this open position is to perform
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spectroscopies, or nanophotonics Basic understanding of data analytics techniques. Preferred Qualifications: Experience with spin-based or squeezed quantum sensors. Experience with dilution refrigeration
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characterization techniques with mechanical behavior and finite element methods. The postdoctoral candidate will develop the processes needed to connect mechanical testing data with 3D microstructure of nuclear
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evolutionary/quantitative/population genetic analyses on existing large datasets. Apply and develop bioinformatic pipelines to analyze diversity data, especially in the context of pan-genome resources. Work
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, analyzing data from complementary techniques such as scanning microwave impedance microscopy, Kelvin probe force microscopy, and cathodoluminescence, as well as collaborating with theorists for data-model
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NCCL. Knowledge of high-performance computing and its applications. Additional Information: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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://www.ornl.gov/directorate/isotopes for more information about ISED. This position resides within the Target Design, Analysis, and Qualification (TDAQ) group in the Radioisotope Production Engineering and Analysis