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statistics for various government and university surveys. (15%) Assist in the execution of all academics-themed student programs, events, workshops, and new student orientation sessions, as well as open house
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school visits on campus and managing group tours on campus, maintaining statistics regarding number of visitors; providing administrative and secretarial support to the Managers; and maintaining an office
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, time, and other resources to pursue independent ideas, including the development of novel statistical methods. full support and assistance with fellowship and research grant applications (e.g. K99
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candidates should have, or be in the process of completing, a PhD (or equivalent) in Biomedical, Electrical or Computer Engineering, Computer and Information Science, Applied Mathematics, Statistics
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Details Posted: 02-Feb-24 Location: New York, NY Salary: Open Categories: Academic/Faculty Internal Number: 120765 Dr. Suzanne Leal's group in the Center for Statistical Genetics at Columbia
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to opportunities to leverage information in these datasets to answer research questions (2) Developing analytical models and performing statistical analysis, including running regressions (3) Monitoring the status
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of the Principal Investigator, Dr. Paris Adkins-Jackson. The Scientist will support several ongoing projects including tasks like data management, and statistical and psychometric analysis with complex survey
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development workshops and seminars (e.g., on statistical techniques, new technologies for research computing, databases, programming languages, etc.) for research staff. Partners with stakeholders including
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statistical records, and other related logs pertaining to the laboratory. Effectively analyzes, trouble shoots and resolves routine technical issues. Assist in setting up, evaluating and trouble-shooting new
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Science, Statistics, Biostatistics, Computational Biology, Applied Mathematics, Computational Neuroscience, Genomics, or Bioinformatics), and extensive experience in standard workflows for analysis of large-scale