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Internal Number: 6415021 Postdoctoral Fellow, Bioinformatics, Brain Tumor Drug Discovery and Development Program University of California Los Angeles Requisition Number: JPF10295 The Brain Tumor Drug
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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and
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Number: 6325358 2027-29 Transfusion Medicine/Clinical Informatics Fellowship University of California Los Angeles Requisition Number: JPF10179 Due to the recent rapid expansion of electronic health records
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Number: 6380165 University of California Irvine Postdoctoral Scholar - Della Martin Fellowship Position overview Salary range: A reasonable estimate for this position is $66,737-$80,034. See Table
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of Physics at the University of Warwick is seeking a highly motivated and talented Research Fellow to contribute to pioneering research in the development of quantum magnetic sensors and advanced imaging
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University of California, Los Angeles | Los Angeles, California | United States | about 22 hours ago
directives may impose additional requirements. The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color
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of the following universities will be accepted. California Institute of Technology University of California, Berkeley University of California, Davis University of California, Irvine University of California, Los
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Role Description A research position is available to support research to enhance observations of human exposure to air pollution and other pollutants using sensor-based approaches. Air pollution is
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, feeding behavior monitoring, and associated visual analytics. Investigate and integrate physiological and behavioral data from diverse IoT environmental sensors for multi-modal stress detection together
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems