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the development and testing of new materials. The work will involve reactor design and setup with gas flow capability and process optimization. Qualified candidates should have a Ph.D. in chemistry, physics
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of reinforcement learning in the brain and leverage these models to assist the experimental groups with experimental design and multimodal data analysis of neurophysiological, causal, and behavioral data
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the operation of a wide range of surface science methods, with emphasis on HRXPS, LEIS, AES, LEED, TPD, HREELS, Raman scattering, and SEM. Qualified candidates should possess experience for the design
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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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/or energy *Strong methodological and quantitative skills, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling
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Research Associates. DDSS supports technical and methodological innovation in quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating
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activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers in
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efficacy of such efforts. Responsibilities will include activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and
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, biologists and visual artists. Responsibilities will include: - Developing a computational Artificial Intelligence design framework based on urban-mined building stock and structural logic, to shape animal
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of nanostructures is a plus. 3. Experimental nanophotonics. Candidates should have significant experience in nanophotonic devices (including nano-plasmonics) design, fabrication, and characterizations. All