145 optimization-nonlinear-functions-"Prof" Postdoctoral positions at Princeton University
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Computational Mathematics invites applications for Postdoctoral Research Associate or more senior positions, to join in research efforts of interest to its faculty. Domains of interest include nonlinear partial
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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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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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the development and testing of new materials. The work will involve reactor design and setup with gas flow capability and process optimization. Qualified candidates should have a Ph.D. in chemistry, physics
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assurance development and data analysis. A successful candidate will work closely in different aspects of the quality assurance and data engineering pipeline, developing usable and innovative solutions
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of existing and novel materials, extensive ex situ (and some in situ) characterization of synthesized materials by materials evaluation tools, and guiding the development and testing of new materials. The work
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postdoctoral research position available in the area of phylogenomics to work with Professor Tiago Simes. The Simes lab is broadly interested in phylogenetic methods and applications, using morphological and
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the guidance and mentorship of one or more core faculty members in the Institute. Work at the Princeton Neuroscience Institute spans from molecular, cellular, and genetic approaches to systems and human
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decision-making and collaboration in young children.The researcher will work with Dr. Natalia Vlez on an on-going research project examining how children incorporate different preferences and perspectives
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bias and inequality.The Postdoctoral Research Associate will work with Dr. Stacey Sinclair on an on-going research project examining how the framing of diversity efforts impacts support for and efficacy