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University of California, San Francisco | San Francisco, California | United States | about 13 hours ago
these insights to improve patient care and reduce false alarms in bedside monitoring. The ideal candidate will leverage their experience with complex data analysis, in particular time-series data analysis
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Monitoring Duties & Responsibilities: Build early warning and clinical deterioration prediction models Develop continuous clinical risk trajectory modeling frameworks Model time-series data such as vitals
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years) in high energy physics, or a related field Experience with applying unsupervised ML algorithms such as autoencoders, clustering, to time-series data is preferred Experience with the data from HEP
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: workshops, lecture series, working groups, and other academic events. Required Qualifications Ph.D. in a relevant discipline, awarded no more than three years prior to the start date. Research agenda focused
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Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly
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. Connections working at University of California Los Angeles More Jobs from This Employer https://main.hercjobs.org/jobs/21898787/project-scientist-series-pool-ad-open-ranks-in-the-department-of-urology Return
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Position Details Position Information Recruitment/Posting Title Postdoctoral Associate Job Category Staff & Executive - Research (Laboratory/Non-Laboratory) Department RSDM - Oral Biology Overview
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position within a Research Infrastructure? No Offer Description A tender is hereby opened for the award of 1 (one) Postdoctoral Fellowship (PDF) under “Reborn - Full human-based multi-scale constructs with
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 10-Jan-26 Location: New York, New York Type: Full-time Categories: Staff/Administrative Internal Number: 554808 Job
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delegated by Order No. 9493/2022, published in the Oficial Gazette, 2nd series, No. 148 of 2 August, for a period of 30 (thirty) working days from the day immediately following the publication of this public