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Science at Johns Hopkins University seeks an outstanding postdoctoral fellow to lead scientific efforts on machine learning applications to signed languages to begin by Fall 2026. The fellow will work
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critically and be innovative. The Department of Computing conducts research across several themes including Machine Learning, Data Science, Intelligent Interactive Systems, Computing in Education and of course
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requirements Essentials: Basic knowledge of power systems and machine learning/AI. Completed an MSc degree in a highly technical related discipline (computer science, electrical engineering, etc.) and you were
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comparative analysis across the cities, identifying common lessons learned and policy recommendations contribute to background working papers, policy briefs and blogs, and participate in workshops and webinars
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About Us For more than 60 years, Kennesaw State University has been known for its entrepreneurial spirit and sense of community. A leader in innovative teaching and learning, Kennesaw State is
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
of scientific articles and the PhD thesis Additional activities : Participation and involvement in the ANR project Scientific mediation and communication Where to apply Website https://jobs.inria.fr/public
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, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the above-mentioned research areas collaboration in national and international research projects, possibly
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Magnetics; Micro and Nano Structures; Sustainable Energy Systems, Power Electronics and Drives; Systems and Controls. To learn more about the Department of Electrical and Computer Engineering at
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, MATLAB, C/C++, etc.) and/or knowledge of holographic imaging is a plus; Prior knowledge and hands-on experience with state-of-the-art machine learning frameworks (e.g., sci-kit-learn, Tensorflow, PyTorch
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neuroscience, psychology, cognitive science, neurobiology, or related disciplines. Peer-reviewed scientific publications. Experience with machine learning, Bayesian statistics, or advanced computational modeling