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monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
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deep learning models using the Oak Ridge Leadership Computing Facility (OLCF) systems. Conduct research with scalable transformer-based foundation models with large volumes of spatiotemporal physical
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Research Description The project aims at combining three primary data sets (JWST NEXUS spectroscopy, Euclid Deep Field North
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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in
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or deep learning reconstructions). Knowledge of radial data acquisition strategies, artifact mitigation methods, and their use in parametric imaging (e.g., T1/T2/T2* mapping). Preferred Qualifications
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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developing new ones, including machine and deep learning methods. There will be opportunities for development of new cell line and animal models and testing, evaluation, and analysis of new genomic
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, implement, and analyze assessments of student learning, affect, and experiences. - Disseminate research outcomes through peer-reviewed publications, conferences, and seminars. - Pursue extramural funding
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Experience Strong background in machine learning, deep learning, or related AI techniques. Proficiency in Python and at least one major deep learning framework (e.g., PyTorch, TensorFlow). Evidence of research
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of ways. CURA’s work ranges from community engaged research to leadership development. Our varied programs seek to develop deep partnerships with community collaborators and acknowledge the expertise