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in Zintellect, they must click the unique link in each email request, but will be given the opportunity to copy over what they had previously submitted. All documents must be in English or include
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. The research focus is on developing and applying first-principles-based and data-driven computational methods to understand multiscale processes and accelerate chemical discoveries for renewable energy
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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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research, technical, or professional skills and experience that are applicable to this opportunity. Availability Details Academic Records: A copy of an official or unofficial transcript or copies
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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searching for a computational postdoctoral research associate. The project is associated with atomistic plasma-surface interaction simulations, employing machine learned interatomic potentials (MLIPs
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atmospheric observations. ● Analyze meteorological datasets and numerical model simulations to investigate mesoscale atmospheric dynamics, convective systems, gravity waves, and precipitation processes
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interactive media, to support faculty and student research in games, simulation, and XR environments. 2. Support faculty in the development and deployment of the front-end and back-end components of a macro
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atmospheric observations. ● Analyze meteorological datasets and numerical model simulations to investigate mesoscale atmospheric dynamics, convective systems, gravity waves, and precipitation processes