54 assistant-professor-and-data-visualization Postdoctoral positions at Cornell University
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will be tasked with creating open data and computational resources for education researchers and developers. The Postdoctoral Associate will participate in a cross-disciplinary research team comprised
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project sites. The research will help gauge views and perceptions of hosting landowners, agricultural and rural community members, developers, and policymakers through qualitative and quantitative data
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project sites. The research will help gauge views and perceptions of hosting landowners, agricultural and rural community members, developers, and policymakers through qualitative and quantitative data
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involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in understanding the drivers
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will be tasked with creating open data and computational resources for education researchers and developers. The Postdoctoral Associate will participate in a cross-disciplinary research team comprised
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cultures, molecular and genetic analysis, and protein analysis techniques. Additionally, we are looking for candidates who demonstrate proficiency in data collection, rigorous data analysis, and effective
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involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in understanding the drivers
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at NIH rates. Anticipated Division of Time 65% of the employee’s time will be spent doing bench laboratory experiments. 15% of the employee's time will be spent analyzing and preparing data
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analyzing and preparing data for presentation 10% of the employee’s time will involve the mentoring of undergraduate or graduate students 10% of the employee’s time will involve professional development
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to facilitate processing and analysis grounded in principles of Responsible AI. In addition, the NTO will be tasked with creating open data and computational resources for education researchers and developers