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. The candidate's work may use empirical or theoretical methods to address important policy questions. The position provides an outstanding opportunity for independent research as well as opportunities
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. Research topics include analysis and astrophysical interpretation of LIGO-Virgo-KAGRA data, forecasting and statistical methods development for next-generation gravitational-wave detectors, and
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, or reading groups), present their work at research methods and field-specific seminars, and offer consultation to faculty, graduate students, and postdoctoral researchers from the social sciences on topics
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Simulation, turbulence closure methods, and/or atmospheric or oceanic circulation/climate models; and c) experience, or demonstrated interest, in machine learning. Candidates must have a Ph.D. or expect to
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uncertainty quantification to improve network robustness. You will design, test, and refine novel methods aimed at understanding the spatial and topological properties of infrastructure networks, with
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experiments and methods. Additional expertise in plasma, plasma-materials interactions, and/or ALE is of significant value. Experience with the design, construction, operation, and maintenance of UHV
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., or equivalent is required. Applicants should have training and a significant track record in one or more of the following areas: -AI, deep learning methods -atmospheric, climate, and/or weather modeling
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experience with both analytic methods and scientific computing. *CV, including complete list of publications. We are seeking to recruit from as diverse a pool of talent as possible, and endeavor to preserve