127 post-doc-image-engineering-computer-vision Postdoctoral research jobs at Princeton University
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Postdoctoral or more senior research positions are available at Princeton University in the laboratory of Professor Celeste Nelson in the Department of Chemical and Biological Engineering to study
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on data science and engineering. The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution earth system model data, with an emphasis on Seamless
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qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range
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, computer science, electrical engineering, applied mathematics, or operations research) before May 2025 are encouraged to apply. Ideal candidates will display outstanding ability for research and a record of
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at Princeton University. The Mesa Lab has pioneered innovative intravital multiphoton imaging techniques, paired with advanced mouse genetic tools, to observe and manipulate immune cell behavior at the single
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The Joseph Research Group at Princeton University is searching for postdoctoral candidates interested in computer simulation studies of intracellular spatiotemporal organization, biomolecular self
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to excellence in education are encouraged to apply. A PhD in Materials Science, Optics, Physics, Chemistry, Electrical, Chemical, Mechanical, Civil or Bio Engineering or related area is required. We
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approach with a focus on cryo-EM. The postdoctoral scholar will have access to cutting-edge cryo-EM instrumentation and computational resources through the various core facilities at Princeton University
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organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro
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; record linkage/entity resolution; data privacy techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine