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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 271598471 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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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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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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following areas: alternative cements (e.g., chemistry of calcium silicate and carbonate cements), physics of diffusion and carbonation, early-stage rheological characteristics, life cycle analysis, and design
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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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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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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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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