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About the Opportunity Postdoctoral Research Associate – Human Data Interaction/Data Visualization – The Roux Institute, Portland, Maine We are currently seeking two postdoctoral research fellows
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behavior, human-computer interaction, psychology, computer science or related disciplines to work on research projects on human-AI interaction. Increasing ability to generate human-AI interaction data needs
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multidisciplinary approach that integrates genomics, transcriptomics, proteomics, molecular biology, and synthetic biology. Key Responsibilities Analyze and interpret multi-omics data to identify stress adaptation
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systems, and analytical methods to meet partner objectives Prepare, analyze, and interpret complex data; disseminate findings through peer-reviewed publications, presentations, and technical reports Write
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data and preparation of manuscripts. In addition, the postdoc will collaborate with the PI in the development and submission of new NSF proposals to extend this research. The position is for 1 year with
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themselves in the United States. A primary goal of this work will be to build interactive data tools that inform the public, policy-makers, and researchers about the impact of municipal court policy and
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the supervision of the PI, including proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. Pursue research topics
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ecosystems. The postdoc will conduct experiments in the field at Yale Meyers Forest and will lead the analysis of resulting data and preparation of manuscripts. In addition, the postdoc will collaborate with
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researchers in experimental techniques and data interpretation. · Collaborate with internal and external partners to integrate discovery data and prepare publications and grant proposals. · Present findings
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vivo evaluations Develop and validate innovative formulations, delivery systems, and analytical methods to meet partner objectives Prepare, analyze, and interpret complex data; disseminate findings