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applications to alternative fuel design and atmospheric chemistry. The successful candidate will be expected to assist with the commissioning of a new shock tube facility and will conduct fundamental
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nanophotonics. Candidates should have significant experience in nanophotonic devices (including nano-plasmonics) design, fabrication, and characterizations. All candidates should have a Ph.D. degree. Appointments
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catalysis, and/or plasma-assisted catalysis is of significant value to participate in other ongoing projects in the lab. Experience with the design, construction, and operation of high-vacuum instruments and
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September 2025. The Ferris group studies high-temperature reaction chemistry and particulate formation using optical diagnostic methods, with applications to alternative fuel design and atmospheric chemistry
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senior researcher in the areas of soft materials and polymer physics. The successful candidate will develop strategies to design, synthesize, and characterize the properties of soft materials using
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, thermal management, and energy conversion. We seek candidates with strong expertise in building and conducting ultrafast time-resolved optical experiments. Key skills include the ability to design, assemble
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., geography, urban planning, data science, sociology, public health, emergency management). Ideal applicants will have: *Expertise conducting spatial and statistical analyses *Experience with scientific
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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, with emphasis on HRXPS, LEIS, AES, LEED, TPD, HREELS, Raman scattering, and SEM. Qualified candidates should possess experience for the design, construction, operation, and maintenance of UHV instruments
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subdivisions of the squamate body plan. The candidate will work towards developing computational resources that assist in the data management and analysis of genomic data and its integration with phenotypic data