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(posted 2025/10/06 05:00 AM UnitedKingdomTime) Position Description: Apply Position Description Sparse Neural Network Design Postdoctoral Research Associate Los Alamos National Laboratory Los Alamos, New
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network and the UPWELLING Academy. This academy will offer specialized training in emerging marine technologies and facilitate prototyping activities, empowering SMEs and startups while nurturing a new
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communications-related performance metrics were considered, such as reliability, connectivity, throughput, delay, network lifetime, power efficiency, and security. In the literature, WSN design is typically
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group and our local, national and international networks Report your results in peer-review scientific publications and international conferences Teach and supervise PhD, MSc and BSc students as
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the impacts of rapid and longer term spatial agricultural shifts, due to international trade networks, on biodiversity, considering losses and gains and how this can be used to allow more direct comparison of
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materials, while having the opportunity to shape a new research capability with broad impact across quantum networking, communications, and computing. Research Focus Design and fabricate superconducting
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on the track of Cyber-Human Physical Systems seeks researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber
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postdoctoral researcher to join the Distributed and Intelligent Connectivity (DISCO) research group, working at the interface between 5G/6G networking and healthcare. The selected candidate will contribute
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of experimental quantum communication hardware development, optical memory qubit characterization, and fiber-based networking demonstrations using novel memory qubits. The goal is to employ the natural telecom
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate