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University of California, Los Angeles | Los Angeles, California | United States | about 16 hours ago
of reproducible bioinformatics pipelines using workflow-management and containerization tools, or high-performance or cloud computing for large genomic datasets. Experience with single-cell RNA-seq analysis using
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-cloud robotic control at our Garmisch-Partenkirchen campus. The project investigates how advanced robotic control and AI-assisted teleoperation can be safely deployed over communication networks with
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experience in cloud computing and utilizing data from the All of Us Research Program are particularly well-suited for this position. Outstanding U of A benefits include health, dental, vision, and life
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aim of EOSC-ARENA is to develop a sovereign, generative and agentic AI environment for scientific researchers, integrated with the European Open Science Cloud. You investigate the impact of AI
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edge-cloud networks. Additionally, the project will develop novel approaches to implement an adaptive approach to policy and governance management across distributed networks based on operating context
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productive scientific results Preferred Qualifications Equipment Utilized High-performance computing; cloud computing; local workstations. Physical Demands and Work Environment Work will be performed in
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of water vapor: How does vapor buoyancy affect the momentum balance and large-scale circulations in Earth's and other planetary atmospheres? How does vapor buoyancy regulate clouds and Earth's energy balance
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further secured by Quantum Encryption techniques. On the other hand, optical links are affected by clouds (overcome by making various sites on the ground available) and turbulence in the atmosphere
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to PhD level in an area related to Computer Science, the applicant will be proficient in software development, systems administration, networking and cloud. This is an invaluable opportunity to develop
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI