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to attract self-motivated and talented researchers who work well in a team environment. The successful candidate will work closely with the labâ™s graduate students and postdocs to develop reproducible
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computational software tools for the lab, support efforts of the research team, train students and postdocs, contribute to data management and analysis, and innovate computational methods for metabolomics
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, distribute keys to incoming faculty, research scholars, postdocs, and graduate students. Maintain an organized key system. Serve as Building Access Coordinator. Assign building access over the summer to all
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the lab’s graduate students and postdocs to develop reproducible bioinformatics workflows for addressing fundamental questions about the ecology and evolution of microbial species within the gut microbiomes
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; Processing raw CT-scan data (e.g., production of 3D volume meshes and segmentation); Training of students and postdocs on the utilization of lab equipment (e.g., stereomicroscopes with Z-stacking, CT-scanner
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computational software tools for the lab, support efforts of the research team, train students and postdocs, contribute to data management and analysis, and innovate computational methods for metabolomics
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coupling, using machine learning. The postdoc will be expected to collaborate with other postdocs at Princeton and with other members of the M2LInES project across multiple institutions. In addition to a
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visiting research scholars and postdocs: Advertise opportunities broadly, respond to questions from applicants, organize applicant materials for review by Centerâ™s Executive Committee, close out searches
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for photosynthetic organisms. Work collaboratively with a postdoc on engineering algal CO2-concentrating mechanism components into the model plant Nicotiana benthamiana. This will include: *Growth of plants under
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Specialist, to develop computational software tools for the lab, support efforts of the research team, train students and postdocs, contribute to data management and analysis, and innovate computational