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experiences that developed or applied at least one of the following techniques to solve a problem related to the broad application areas as listed above: signal processing/time series analysis, machine learning
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in electrical and computer engineering, including physics, mathematics, signal processing, and machine learning demonstrated by a relevant Ph.D. degree and a scholarly record. For more information on
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-funded project to help improve early diagnosis of ASD by using cutting-edge tools from machine learning and computational ethology. Project Motor differences are one of the earliest markers of increased
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to conduct research on developing and using machine learned parameterizations developed from ocean-data assimilation increments. The goal is to develop parameterizations of unresolved processes that will
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We are looking for a scholar with research interests in applications of machine learning to health, interested to pursue a Postdoctoral Fellowship at Stanford University, School of Medicine in Palo
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applications at the intersection of statistical mechanics, multiscale simulation, and machine learning. The successful applicant will be appointed through the Chemical and Biological Engineering Department
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team for an exciting NSF-sponsored project. This research focuses on the integration of spatial computing, AI/machine learning, data science, and human factors engineering to advance our understanding
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literal contributions to the scientific community. CORE JOB FUNCTIONS Develops and implements advanced computational and machine learning methods for the analysis of large-scale omics data, including
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. The project will focus on research and development of advanced machine learning and deep learning algorithms to analyze large quantities of multimodal images and data arising from the Advanced Plant Phenotyping
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, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual