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command of English (min. B2). Preferred: • Experience in C and data engineering; • Previous experience in database development and/or maintenance; • Knowledge of Large Language Models (LLMs) applied to data
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases
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University of California, Los Angeles | Santa Monica, California | United States | about 14 hours ago
, patients and staff Skill in quickly assimilating and retaining a large body of financial screening and patient registration information Working knowledge of hospital/billing forms and the
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with computational scientists to integrate and interpret large-scale genomics data. Present research findings in lab meetings, departmental seminars, and conferences; prepare manuscripts and fellowships
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on the application of genomics and other omics data to improve clinical care, with an emphasis on cardiovascular disease and personalized medicine. Dr. Matthew Wheeler's research centers on the integration of large
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. Certified Energy Manager 1-2 years experience with maintenance and incremental improvement of large scale excel models using time series data, energy unit conversions and coefficient of performance
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collection challenges (e.g., technology, logistics, respondent recruitment). Data Management & Analysis Clean and manage large-scale quantitative survey datasets using R (preferred) and Stata or other packages
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Risk Management, the University Police Department, Academic Affairs, Enrollment Management, and University Communications. The AVP provides direction for the department’s assessment and data strategy
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development, engineering big-data systems, and engineering secure software systems. MS in Information Systems Bridge is focused for students with non-STEM, non-technical bachelor's degrees
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applications, query tools, and relational databases, in order to extract data from existing systems, join large datasets, manipulate data (e.g., import data, transform and derive variables), and aggregate data