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semester, assist in organizing research-based events (e.g., speaker series, symposia, or reading groups), present their work at research methods and field-specific seminars, and offer consultation to faculty
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spectroscopic and imaging techniques for UHV surface science experiments and methods. Additional expertise in plasma, plasma-materials interactions, and/or ALE is of significant value. Experience with the design
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*An interest in mixed-methods approaches, including also qualitative and case study approaches *Strong collaborative skills and ability to work well in multidisciplinary environments. *Excellent verbal and
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superconductors. The successful candidate must have substantial experience in state-of-the-art ARPES and/or low temperature STM/STS techniques. Some experience with first-principle methods (FP/DFT) and/or other
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, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling *An interest in mixed-methods approaches, including also
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include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with computational models, programming, and quantitative methods
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) understanding and controlling interfaces for lithium-metal batteries, and iii) synthesis and characterization of catalysts for plasma-assisted catalysis. Research involves synthesis and characterization
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System for Prediction and EArth System Research (SPEAR) for seasonal to multidecadal prediction and projection. The project will emphasize elements such as stakeholder engagement, earth system model
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modeling methods and tools. Applicants should have strong, demonstrated research ability, and excellent English written and spoken communication skills. Preference will be given to applicants with
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modeling methods are encouraged to apply, including but not limited to integrated assessment modeling, energy system modeling, climate and air quality modeling, and agent-based modeling. All candidates must