83 algorithm-development-"Multiple" Postdoctoral research jobs at Princeton University
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starting July 2025, and will remain open until excellent fits are found. The successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine
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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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scientists for research and development activities focused on data science and engineering. The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution
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until excellent fits are found. The successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine learning (AI/ML) being a major focus
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Department, an innovative, collaborative, and vibrant research environment. Princeton University is in an idyllic college town halfway between New York City and Philadelphia, with convenient train access
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researchers working on an NIH funded project focused on developing new systems models to examine social and biological drivers of infection inequality. The overarching goal of this postdoctoral position is to
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The Department of Electrical and Computer Engineering has opening for postdoctoral research positions in the following fields: 1. Microfluidic and Lab-on-Chip development in a multidisciplinary lab
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days per week. Leveraging Princeton's scholarly resources, fellows will focus on research, expand their intellectual horizons, and prepare work for publication. They will have biweekly meetings with
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addition to the aforementioned project, the appointee will have opportunities to develop additional projects with members of Dr. Sinclair's lab and/or maintain their on-going work. The work location for this position is in-person
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion