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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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; proficiency in graph data structures and algorithms for geometric analysis; advanced knowledge of surface representation math; experience in writing geometry translators for complex surface features; excellent
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analysis. Required Education: PhD in Engineering Education or a related field. Desired Education: PhD in Engineering Education or a related field Required Experience: •Conducting and analyzing interviews
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in materials physics and defect properties Required Education: PhD in Materials Science and Engineering Required Experience: Experience with VASP and high-performance computing; A background in
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; collaborates with principal investigator (PI) to develop and implement goals and objectives of studies; develops algorithms for medical image reconstruction, including but not limited to computed tomography
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driving systems; assists in the integration of sensors and perception algorithms; assists in the design of software pipeline and experiments; performs and monitors experiments and data collection; assists
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candidate will demonstrate a record of excellence in one or more core areas of quantum information, such as quantum computing, quantum algorithms, quantum simulation, quantum networks, or quantum sensing
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instrumentation. It involves supervising the research of graduate students and REU’s, conceiving, composing, writing and editing research proposals, scientific papers and research reports. Required Education: PhD
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biochemistry is preferred. Experience in RNA processing is desirable. Candidates should have a Ph.D. or MD/PhD in cell biology, cancer biology, molecular biology, or biochemistry. Knowledge and expertise in
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undertaken. Minimum Required Qualifications: Ph.D. in wildlife management, biology/ecology, ecosystem or environmental science, or a related discipline At least 1 year post-PhD degree with experience