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University of California, San Francisco | San Francisco, California | United States | about 3 hours ago
, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems. Ability to represent relevant information in abstract models. Critical
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will have the opportunity to learn and apply advanced data analysis techniques, including machine learning and econometric modeling. Through collaboration and technical expertise, this position supports
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/Master’s degree in statistics, mathematics, computer sciences or a related field Thorough knowledge of methods in event history analysis and multi-state models is required. The candidate should be familiar
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, supply chain systems, and transportation systems. We also currently host methodological research in data analytics, machine learning, human systems engineering, optimization, simulation, and stochastic
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, early detection of degradation, and residual life prediction. The program integrates physical modeling, machine learning, and data fusion techniques to optimize predictive maintenance, reduce operating
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the Job related to staff position within a Research Infrastructure? No Offer Description Job Purpose As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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blood samples to advance patient care. This role will involve developing computational models (statistical, machine learning, etc.), and using them to perform high throughput analysis of clinical data
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technical specifications. Knowledge, Skills, and Abilities: Advanced applied statistics skills, such as distributions, statistical testing, regression, etc. Professional experience developing machine learning
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Grade Level 41 Salary Range $15.83-25.30/hour Type of Position Staff Position Time Status Full-Time Required Education HS Click here for more information about equivalencies: https://hr.uky.edu/employment
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling