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Field
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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Line of research: "Research in secure and intelligent distributed computing" published in the official gazzette BORM 23/10/2025. ( IN SPANISH). Where to apply Website https://convocum.um.es/convocum2
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see our homepage: https://www.combustionphysics.lu.se Our division has a good atmosphere/tradition of collaboration. The metal combustion project will involve many expertise and effective collaboration
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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furnace simulator, you will study the interaction, distribution and impact of alkalis and sulfur across BF and gas-based DR reactors. Their behaviour in direct reduction remains largely unexplored, making
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Robotics. Further information Please visit us on LinkedIn: https://www.linkedin.com/company/sdu-robotics . Further information about this position is available via email to Assistant Professor Di Wu diwu
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UVP (Underwater Vision Profiler) database including Particle size distribution (PSD) and concentrations from ship-based rosette deployments, BGC-Argo profiles, gliders, moorings, and other platforms
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work within the ADAPTING PEPR project, funded by France 2030 and led by the ANR (French National Research Agency). Within this project, the ASIC team at IETR aims to develop a distributed platform for
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: Professor Zhongwen Zhan) to design, build, and validate a miniaturized Distributed Acoustic Sensing (DAS) system for the lunar environment. Key responsibilities: - Architect and prototype a low-SWaP (Size
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning