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of supporting documentation across various platforms (e.g., REDcap, Qualtrics); Build, design, and manage databases using MySQL or MS Access; Use R, Python, SAS, and/or Access to integrate data from multiple
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. The candidate will work closely with faculty, staff scientists, and trainees across multiple institutes and departments, contributing to high-impact publications, software tools, and collaborative grant proposals
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admissions data to streamline and optimize decision-making processes. The position requires excellent organizational skills, attention to detail, and the ability to manage multiple priorities and deadlines
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proficiency in teaching and/or using a coding-based statistical program is required. Proficiency with multiple analytical tools and approaches, including R and/or Python, for use in big data techniques is
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Oracle Campus Solutions architecture and PeopleSoft applications. Project management experience; ability to track multiple projects, set priorities, and meet deadlines with frequently changing priorities
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multiple other departments. The U-M at Ann Arbor provides an outstanding training environment for researchers and very attractive benefits packages to its employees. Ann Arbor is one of the most educated
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multiple options for the technical direction for projects. Convey progress and challenges to the MCT2D program manager. Communicate with internal stakeholders (PMs and Design) and collaborators on technical
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. Ability to work independently, prioritize multiple projects, and achieve objectives by required deadlines while maintaining high-quality outcomes. Hold or be willing to obtain industry leading
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. We use Python, JavaScript, Django, PostgreSQL, and related frameworks to build frontend and server applications for deployment in multiple customer environments. The ideal candidate would demonstrate
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of multiple and sometimes conflicting data sources, periodic review of dashboards and reports for accuracy; manual review of medical records to resolve data concerns and ensure accurate information and data