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The opportunity The University of Liverpool is a key partner in a £14 million initiative ( https://tinyurl.com/yc5z768m ) to develop a sustainable, next-generation manufacturing facility, using
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algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project “Utility Optimization in Quantum Networks: Algorithm Design and Analysis”, working with Dr
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conditions. Work Plan Description Objectives: The main objective of this research project is to use real 2D data to optimize the workflow of FWI inversion algorithms. Methodology: 2D seismic data will be used
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national and international reference point in quantum technology research. The integrated approach—which combines experimental development, numerical simulations, and advanced algorithm design—will create a
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and data-driven frameworks for battery management systems, including health monitoring, early fault detection, and safety-oriented control algorithms. Investigate thermal management, fire suppression
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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Prof. Youngseok Kim (Ohio State University) – Quantum Computation & Quantum Algorithms Prof. Pilkyung Moon (NYU Shanghai) – Graphene, Twistronics, Novel Topological Materials Website of our team https
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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward