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? No Offer Description Mission: Adapt simulators for electromagnetism, electronics and computer architecture and perform simulations in these areas. Functions to be developed: Provide support for
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-transparent materials, and the utilisation of deep learning algorithms to accelerate computational solutions. Scientific Objectives Develop a self-contained finite volume solver for solidification of multiphase
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of pinching plasmas. This research associate will work with the Michigan State University (MSU) team to develop new scalable algorithms inside of the Parthenon framework, an AMR performance portable framework
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Nantes, Pays de la Loire | France | about 8 hours ago
evolutionary processes in aquatic environments and their interfaces, from headwaters to the ocean, assessing ecosystem status, and developing scenarios for their future evolution. The PhD project will be
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. Research Tasks and Training Objectives The doctoral candidate will: Develop numerical and data-driven models for thermoelectric coolers used in on-chip cooling applications Apply optimisation algorithms
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algorithms have been developed, most based on a hybrid architecture combining transform coding and predictive coding. Standards such as H.264/AVC, HEVC, and VVC follow this principle. While they offer highly
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Senior Research Scientist to design and develop
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Engineer to conduct research on air traffic management (ATM) algorithms and
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project focuses on the development of advanced models and algorithms
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of this thesis focus on several key areas: - Detection and modeling of node mobility: Supervised learning models will be developed to identify mobility patterns based on radio indicators such as RSSI, SNR, and