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Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited states and
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are looking for: PhD degree in Chemistry, Biochemistry, Chemical Biology, Material Science, or related areas. Relevant experience in protein purification, characterization, and bioconjugation. Familiarity with
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reasoning over large scientific data sets. Developing theories for materials synthesis and degradation. Preparing presentations and reports. Writing peer-reviewed journal articles. We are looking for: PhD in
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studies on quantum materials and complex oxides, with an emphasis on microelectronics applications. In addition to experimental work, the role includes applying machine-learning and AI-based approaches
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development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction
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to access Berkeley Lab sites (for more information click here ). Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Equal Employment Opportunity Employer: The foundation