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innovative materials for transportation infrastructure with applications in civil (geotechnical/material) engineering, industrial scale economics, and transportation infrastructure performance. The successful
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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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, privacy, and security. Activities often address applications in wide-ranging areas, including biology, robotics, cyber & physical security, economics, voting, engineering, ecology, sociology, epidemiology
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date of May 2026 in Dr. Nicole Fahrenfeld’s group in Civil & Environmental Engineering at Rutgers University-New Brunswick (https://sites.google.com/site/nicolefahrenfeld/home ). The postdoc will lead
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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related field (e.g., Atmospheric Science, Remote Sensing, Earth Science, Environmental Science, Environmental Engineering) by the time of appointment. Background in atmospheric remote sensing is strongly
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. Posting Summary A postdoc position is available immediately in Dr. Yalin Li’s group in Civil & Environmental Engineering at Rutgers University-New Brunswick (https://yalinli.group ; https://cee.rutgers.edu
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. Posting Summary A postdoc position is available immediately in Dr. Yalin Li’s group in Civil & Environmental Engineering at Rutgers University-New Brunswick (https://yalinli.group ; https://cee.rutgers.edu
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group in Civil & Environmental Engineering at Rutgers University-New Brunswick (https://yalinli.group ; https://cee.rutgers.edu/yalin-li ). The postdoc will lead research on process design, techno
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this position will be to work as part of an interdisciplinary team spanning across the colleges of engineering, medicine, and science. The successful candidate will be required to lead independent research