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University of Tennessee Medical Center at Knoxville | Knoxville, Tennessee | United States | about 16 hours ago
of the fellowship, participants will participate in networking opportunities, leadership development and community outreach. Highlights of the program include: One year program Cohorts starting in January and July
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Science Group: Telecommunications and Networking - Av Work Objectives: 1 – Analysis of the state of the art in federation mechanisms on Multi-access Edge Computing environments 2 – Analysis of advanced
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Communication), • ACM MobiCom (International Conference on Mobile Computing and Networking) • ACM MobiSys (International Conference on Mobile Systems, Applications, and Services) • USENIX (Advanced
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requirements PhD in Physics, Applied Mathematics, Computational Science, or a related field Strong background in machine learning, particularly in the development and application of neural networks
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aim of this programme is to facilitate and strengthen collaboration with academic researchers in scientific fields that are priorities for France and Canada, as defined at the first Joint Committee
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for accurate localization and tracking of 5G network User Equipment (UE) in urban environments. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Study 5G protocol and implementation
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Elgammal, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone, CAN: Creative Adversarial Networks, International Conference on Computational Creativity(ICCC), 2017 Theme B continual learning (selected papers
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We invite applications for multiple Postdoc positions in the Accelerated Connected Computing Lab (ACCL) at KAUST! The new research group, supervised by Suhaib Fahmy explores hardware acceleration
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postdoctoral researchers whose interests and expertise align with our values and the needs of the network. These positions will be co-developed based on alignment between applicant, and the project and program
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fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can