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PhD in a related field (e.g., statistics, computer science, electrical engineering, applied mathematics, or operations research), before September 2024, are encouraged to apply. Ideal candidates will
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-principles modeling and machine learning. The center is seeking a qualified candidate with a Ph. D. in physics, chemistry, engineering, applied mathematics, and related disciplines, having a strong
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. Required Qualifications: Ph.D. in a relevant science or engineering field is required. Candidates from subsets of fields including hydrology, scientific computing and applied mathematics are particularly
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this position is required. Candidates from subsets of fields including atmospheric and climate sciences, computer science, physics and applied mathematics are particularly encouraged to apply. Experience with
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. Candidates from subsets of fields including atmospheric and climate sciences (particularly in the subdisciplines of atmospheric chemistry and atmospheric/climate dynamics), physics and applied mathematics
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engineering field is required. Candidates from subsets of fields including hydrology, scientific computing and applied mathematics are particularly encouraged to apply. Experience in hydrologic/hydraulic
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required. Applicants should have a background in cognitive science or a related discipline such as computer science or psychology, with a research agenda focused on using mathematical, computational, and
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, instrumentation/device design (e.g. optics, microfabrication), quantitative light microscopy, and computational work or mathematical modeling would be useful. Princeton University is committed to diversity, equity
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biology, applied mathematics, statistics, or an equivalent discipline. Additional experience in climate, meteorological, or environmental data analysis or related topics is highly desirable. Candidates
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cosmology, condensed matter, mathematical, and particle physics. Candidates for the position must have a Doctorate degree in Physics or a related discipline. Positions are funded for one year with