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to create the world’s largest open-access dataset of tutoring (the Million Tutoring Moves [MTM] dataset), along with open-source applications that support data processing and analysis grounded in Responsible
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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their
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serves the computational and data analysis needs of the Cornell community and their collaborators from science and engineering and the humanities. CAC serves the national community as a partner on the NSF
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farm families, financial analysis tools, and applied research along with strong sense of teamwork will be necessary to facilitate business focused discussion groups as part of the management education
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recycling. Insights gained will also be applied to the development of sustainable terrestrial biotechnologies addressing the plastic crisis, carbon revalorization, critical metal recovery, and circular
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open-access dataset of tutoring (the Million Tutoring Moves [MTM] dataset) and open-source libraries to facilitate processing and analysis grounded in principles of Responsible AI. In addition, the NTO
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the plastic crisis, carbon revalorization, critical metal recovery, and circular bioeconomy approaches on Earth and in space. We are looking for an experienced scientist in bioengineering, molecular biology
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secondary data sources for research; use and analysis of quantitative data in concert with extensive in-depth literature reviews and related written summaries targeting AI topics; completion of human subjects
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with a dissertation that includes a focus on host-microbe interactions, microbial community analysis, or microbial metabolism. Demonstrated expertise in one or more of the following: microbiome
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position requirements. Your letter is an important component of your application. When evaluating your candidacy, we will look for evidence of the following: Bachelor’s degree in business, finance