225 computer-science-intern "https:" "https:" "https:" "https:" positions at The University of Chicago
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protocols and internal SOPs. Accountable for high standards of clinical research practice and assists in the development of accountability in others. Develops and implements procedures, maintains records
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. In addition to their numerous outcomes-based research projects, our investigators are busy with complex basic science questions that will one day allow physicians to deliver better care to all patients
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the Teaching Fellows Program. The terms and conditions of employment for this position are covered by a Collective Bargaining Agreement between the University and the Service Employees International Union (SEIU
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engagement goals with the mandate to oversee enabling infrastructure of the University including the built environment, technology, and human resources organizations. In support of faculty, students, and staff
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Sciences Division at the University of Chicago Medicine. CCHE aims to eliminate all new HIV transmission events by 2041. The University of Chicago's position on the South Side makes it uniquely situated
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of computing hardware, and interaction with hardware and software vendors as required. Maintains a high level of awareness of current issues in technology and engages in continuing education. Guides a variety of
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executing events. Technical Skills or Knowledge: Demonstrated skill and knowledge of, or ability to learn quickly, the internal workings of the University as well as the technology tools available
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others, both on internal teams and with external partners. Excellent organizational skills and attention to detail. Ability to learn new lab protocols and apply them at scale (e.g. genotyping thousands
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and impactful research in various domains, including the Biological Sciences. The Biological Sciences Division is at the forefront of cutting-edge research and the Research Administration Office plays a
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Qualifications Education: Ph.D. in computational biology, bioinformatics, statistics, computer science, AI/ML, or a related quantitative field. Experience: Experience in either: Large-scale genomics data analysis