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researchers at Princeton and other institutions, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with
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of the work builds on recent publications from the laboratory, e.g. integrating language models with mass spectrometry data (https://www.nature.com/articles/s42256-021-00407-x, https://www.nature.com/articles
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commitment to interdisciplinary research are especially encouraged to apply. Responsibilities will include: - Developing a computational Artificial Intelligence form finding design framework to shape
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who are unable to upload unofficial transcripts may send official transcripts to Politics Postdoc Search, Department of Politics, 001 Fisher Hall, Princeton University, Princeton, NJ 08540. A PhD is
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senior researcher in the areas of soft materials and polymer physics. The successful candidate will develop strategies to design, synthesize, and characterize the properties of soft materials using
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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. These models will be used to design and test policy and investment interventions to alleviate deployment bottlenecks. The successful candidate will have experience with applied energy systems analysis, economy
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their residency at Princeton to assisting with research and to their own work. Eligible candidate must have less than five years of post-PhD research experience prior to anticipated start date. This is a one-year
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Princeton University's Initiative for Data-Driven Social Science (DDSS) invites applications for Postdoctoral Research Associates. DDSS supports technical and methodological innovation in
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials