110 civil-engineering-soil-structure-interaction Postdoctoral positions at Princeton University
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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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The Koel laboratory in the Department of Chemical Engineering at Princeton University is seeking a postdoctoral or more senior researcher position for new projects to characterize synthesis
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design and structure, and bioengineering applications. Candidates should have recently received or are about to receive a Ph.D. or doctorate degree and have a strong interest and track record in designing
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senior ranks may have multi-year appointments. A PhD is required, with appropriate research experience in quantitative biology, (bio)physics, (bio)engineering or related Engineering and Physical sciences
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the Department of Chemical and Biological Engineering to study the biochemical and mechanical mechanisms that define pattern formation during branching morphogenesis of the lung and mammary gland. Further
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: 270175780 Position: Postdoctoral Research Associate Description: The Department of Mechanical and Aerospace Engineering is seeking candidates for postdoctoral and more senior research positions. Individuals
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, with appropriate research experience in quantitative biology, (bio)physics, (bio)engineering or related Engineering and Physical sciences disciplines, and a solid publication record. We seek faculty
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. Essential qualifications for this position include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with computational
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research levels in the areas of biochemistry, biophysics, cell biology, structural biology, microbiology, developmental biology, virology, genetics and cancer biology. The term of appointment is based
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757