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application teams and contribute to broader initiatives, including the American Science Cloud (AmSC) AI Services efforts, and to help us with design of future systems and data-management solutions to meet needs
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WaterWeave project, which focuses on innovative solutions for monitoring and the sustainable management of water resources. The fellow will develop machine learning and cloud computing techniques to estimate
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skills. Experience with cloud computing and big data analytics platforms. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer. PD; SN Requisition ID: 23791 Apply now
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, NY, invites applications for a Postdoctoral Associate in Health Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support
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to marine terminating glacier stability, changes in iceberg calving behaviour, and the trajectories and lifespans of icebergs. This will involve working with satellite data currently held in the cloud
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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University of Applied Sciences in Nowy Sacz (Akademia Nauk Stosowanych w Nowym Sączu) | Poland | about 1 month ago
teaching in the field of computer networks, system and network security, cybersecurity of IT systems, and security of cloud systems and services, 4) the ability to work effectively in a team, 5) willingness
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sensing. Familiarity with High-Performance Computing (HPC) and/or Cloud computing (openEO) Why Join Us? Work on high-stakes climate research projects with global impact. Access to state-of-the-art EO data
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(meteorological, hydrological, hydraulic, traffic, LiDAR, and DEM/BLE datasets). Build reproducible pipelines in Python/R/Julia/SQL for big data geospatial applications. Utilize cloud and HPC resources for model