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associate position is available in the laboratory of Heather Feaga at Cornell University for a highly motivated candidate to study the role of ribosome quality control in the model spore-forming bacterium
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of Heather Feaga at Cornell University for a highly motivated candidate to study the role of ribosome quality control in the model spore-forming bacterium Bacillus subtilis . The candidate will develop a
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ability to publish peer-reviewed research Experience developing reproducible analytical workflows and collaborative codebases using version control Supervision Exercised The incumbent will have
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that advances the Program's mission. Applicants must have completed the Ph.D. by January 1, 2027. Selection will be based on the quality and promise of the applicant's research, record and promise as a teacher
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, greenhouse, controlled-environment, and field experiments evaluating seed coating integrity, delivery characteristics of plant defense signaling compounds, and interactions with seed pathogens and early-season
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benchmark for auto-formalization of mathematics, and to engage in related research. Duties will include contributing to the benchmarking dataset, organizing and ensuring the quality of the data contributed by
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complex datasets Develop final publishable-quality tables and figures for inclusion in research manuscripts Write and clearly document research code to clean, maintain, and analyze datasets Manage data
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, NY. Postdoc position responsibilities will include: • Conduct epidemiological and statistical analyses of large complex datasets • Develop final publishable-quality tables and figures for inclusion in
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for advanced data analysis and/or experimental control (e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in
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administer a benchmark for auto-formalization of mathematics, and to engage in related research. Duties will include contributing to the benchmarking dataset, organizing and ensuring the quality of the data