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presentations. Position Requirements Ph.D. completed in the past 5 years or soon to be completed in Molecular Biology, Biochemistry, Structural Biology, Biotechnology, Protein Engineering, Microbiology, or a
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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. Position Requirements Ph.D. completed in the past five years or soon-to-be completed in Chemical Engineering, Materials Science, Chemistry, Nuclear Engineering, or related field. Skill in devising and
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models for composites of arbitrary structures to predict their homogenized properties. The candidate will also work closely with AI experts to develop workflows for composite structure discovery given
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of chemical and electrochemical principles to control and improve product morphology, product quality, and process efficiency at engineering scales. With guidance, the appointee will : Develop novel process
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morphology, product quality, and process efficiency at engineering scales. With guidance, the appointee will : Perform experiments with multimodal sensors to advance the technical understanding and application
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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The Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering
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and unravel structure-function relationships. This position is suited for a highly energetic and self-driven researcher willing to work in highly collaborative teams. This position will involve a
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recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Computational Materials Science, Chemical Engineering or a closely related field. 2. Technical Expertise