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We are seeking a Postdoctoral Appointee - Data Management Techniques for AI/Machine Learning. A candidate with expertise at the intersection of HPC and AI. Major efforts at Argonne in this direction
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electroencephalographic (EEG) signals, which capture the brain's neuroelectrical activities. The research will employ both conventional biosignal processing techniques and AI/machine learning methods to characterize
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. We're seeking someone with a passion for developing new algorithms, mathematical formulations, machine learning models, and robust systems that will help enhance the scene representation, understanding
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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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learning and machine learning. Presents the advancements to Prof. Liu and his collaborators. Develops cutting edge deep learning systems. Publishes research papers in the top-tier conferences. Presents
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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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individuals with a strong background in AI, machine learning, and deep learning, who are passionate about tackling current health research challenges. Essential qualifications include: A solid understanding of
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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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fellow. Highly motivated individuals with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing
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The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning