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and requirements in a hybrid and cloud-centric environment (e.g. AWS Bedrock, Azure Foundry, Copilot, Power Platform). An understanding of Cloud, Managed Service and integration architectures for AI and
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knowledge of existing and emerging technologies, including public cloud offerings from Amazon Web Services, Microsoft Azure, and Google Cloud. Acts as a technical consultant and resource for faculty research
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of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department Description University of California, San Francisco
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enterprise-level technology projects (e.g., CRM, ERP, infrastructure, cloud systems). Proven ability to lead diverse project teams, set direction, communicate vision and influence outcomes without direct
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d) Your tasks: Support in processing satellite and UAV remote sensing data on cloud platforms Adaptation and optimization
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abundance of computation power residing in the network. The focus in our group is research, development and implementation of networking and edge/cloud computing solutions, primarily in the context of 5G and
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Skip to Main Content Toggle navigation Home Search Jobs Job Alerts Log In /Create Account Help Assistant Professor in Cloud Computing Bookmark this Posting Print Preview | Apply for this Job
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. Excellent organizational/record-keeping skills. Excellent interpersonal skills. Competence with computer programs such as Microsoft Office, Adobe Creative Cloud. Desired qualifications. Previous experience
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astronomy. We develop and operate commercial-quality, cloud-based software application and platform services used by 10s of thousands of researchers to manage their large–and growing–data management