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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
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some of the following areas: molecular dynamics, Monte Carlo simulations, statistical mechanics, computer programming (e.g., C++, Python), polymer theory, molecular modeling (e.g., of proteins, nucleic
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positions to work in experimental condensed matter physics with focus on angle-resolved photoemission (ARPES) and scanning tunneling spectroscopy (STS/STM) based studies of topological, strongly correlated
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, and protein engineering. The group is part of the Department of Chemical and Biological Engineering (https://cbe.princeton.edu/). Qualified candidates will be highly motivated, with a strong
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background check. The work location for this position is in-person on campus at Princeton University. Appointments are for one year with the possibility of renewal pending satisfactory performance and
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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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to maximize their potential to explore, discover and understand emergent behavior of complex quantum matter. The Moore Postdoctoral Scholars in Theory of Quantum Materials program is an integral part of EPiQS
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: The condensed matter spectroscopy group at Princeton University invites applications for multiple Postdoctoral Research or more senior positions to work in experimental condensed matter physics with focus
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The condensed matter spectroscopy group at Princeton University invites applications for multiple Postdoctoral Research or more senior positions to work in experimental condensed matter physics with
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boundary layer and apply them to ocean climate models. Our previous work demonstrated that neural networks can learn to predict the vertical structure of vertical diffusivity and the networks can then be