109 distributed-algorithm-"Meta"-"Meta"-"Meta" positions at The University of Chicago
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, proteomics and genetic data. Assist in creating data algorithms and specialized computer software to identify and classify components of a biological system (i.e. DNA, RNA, and protein sequences). Produce
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scalable machine learning algorithms for a variety of research projects. Manages project teams and junior staff, leads task supervision and quality oversight. Works with partners to identify analytical
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in both individual and group settings. Develops original content for career related publications and assists with the editing and distribution of Career Services communications materials. Performs
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experience. Beyond these duties, the position manages expense reimbursements and provides event support for departmental workshops. This role also assists with workload distribution across the administrative
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growth and lead succession planning initiatives. Ensures robust day-to-day infrastructure operations, including power distribution, cooling, environmental controls, cybersecurity, and automation. Drives
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. Provides administrative support to Study Abroad leadership team, as necessary. Records and distributes weekly staff meeting minutes. Manages file maintenance for study abroad programs and special projects
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when diplomas are created and distributed. This role liaises with students, staff, and University partners, produces official documents and statistical reports, and certifies student records. Through
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clinical operations at our regionally distributed hospital/clinic sites. The Department has an extensive cancer biology research program, and the appointee is expected to develop collaborations between
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responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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, the assistant will preprocess raw omics data, conduct exploratory and multivariate analyses (e.g., PCA, CCA), and iterate on new algorithms for mutant detection and pathway discovery. The role is ideal for a