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, materials science and engineering, chemical engineering, or in a relevant engineering field, with an extensive background and training in the operation of a wide range of spectroscopic and imaging techniques
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://puwebp.princeton.edu/AcadHire/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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"Ferris Lab Postdoc Inquiry 2025". Applications will be reviewed on a rolling basis, until the position is filled. Expected Salary Range: 65000-70000 The University considers factors such as (but not
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. in chemistry, physics, materials science and engineering, chemical engineering, or in a relevant engineering field, with an extensive background and training in the operation of a wide range of
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, mathematical approaches to signal analysis, information theory, structural biology and image processing. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with
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processes for data standardization, data warehousing, quality assurance development and data analysis. A successful candidate will work closely in different aspects of the quality assurance and data
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at Princeton University. The Mesa Lab has pioneered innovative intravital multiphoton imaging techniques, paired with advanced mouse genetic tools, to observe and manipulate immune cell behavior at the single
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
and atmosphere components of existing coarse resolution IPCC-class climate models, and their coupling, using machine learning. The postdoc will be expected to collaborate with other postdocs
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engineering, or in a relevant engineering field, with an extensive background and training in the operation of a wide range of spectroscopic and imaging techniques for materials characterization. Use of HRTEM
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development, service delivery with an overarching objective connecting science with society. This encompasses the development of infrastructure and processes for data standardization, data warehousing, quality