141 postdoc-density-functional-theory-dft Postdoctoral research jobs at Princeton University
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757
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/acad-positions/position/36402 and submit a cover letter, CV, a research statement that includes your specific plans and goals for advancing equity and inclusion if hired as a Princeton postdoc, and
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, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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part of the Gordon and Betty Moore Foundation's Emergent Phenomena in Quantum Systems initiative (EPiQS) The initial appointment will be for one year, with the possibility of renewal up to three years
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develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other researchers at Princeton and other institutions
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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performance and continued funding. Postdoctoral Research Associates (PDRAs) are expected to be in residence at Princeton or the local vicinity for the entire academic year or demonstrate to the program's
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Mechanical Engineering, Aerospace Engineering, Chemical Engineering, Chemistry, or a related field is required. The appointment will be for one year with possible renewal based on performance and available
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Engineering, Chemistry, or a related field is required. The appointment will be for one year with possible renewal based on performance and available funding. This is a full-time position; work must be
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differential equations, computational fluid dynamics, material science, dynamical systems, numerical analysis, stochastic analysis, graph theory and applications, mathematical biology, financial mathematics