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is Computing Continuum (Cloud To Edge), which addresses activities related to the orchestration of distributed resources in heterogeneous environments (HPC/Cloud/EDGE) with a focus on the use of energy
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at least two (2) years working on large scale cloud-based projects; (Bachelor's degree in computer science, information technology, or related field, can substitute 1-year experience, Master?s Degree can
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, benefits, etc., are currently subject to negotiation with the appropriate union. To learn more about the benefits of working at UCSF, including total compensation, please visit: https
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program and the MD/PhD program are located on the Twin Cities campus in addition to MD programs at regional campuses in Duluth and St. Cloud. Pay and Benefits Pay Range: $62,232 annually; depending
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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 2 months ago
17 Jan 2026 Job Information Organisation/Company EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites Research Field Computer science Environmental science Physics
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19 Mar 2026 Job Information Organisation/Company IMDEA Networks Institute Department Networks Data Science Group Research Field Computer science » Other Researcher Profile First Stage Researcher (R1
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III is responsible for implementing and supporting cloud services across a variety of computing environments. Leads the deployment of highly available and fault-tolerant enterprise and web-scale
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qualified talents. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Trustworthy AI, secure and reliable systems, cloud computing, cryptography, network
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dashboards and visualizations using Tableau. • Exposure to cloud-based data platforms or big data technologies. Additional Posting Information: JMU’s Dual Career and Community Resources Program is available
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-design to enable efficient and accurate deployment of AI algorithms on robotic, edge, and heterogeneous computing platforms. Develop methods for efficient deployment of AI models on cloud and edge devices