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dynamic workloads, while bridging theoretical research with practical implementation through close collaboration with cross-functional teams. Job Description: Conduct cutting-edge research in cloud
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research, education, and services in data science, AI, and biomedical computation. We invite applications for a Research Asisstant (Cloud Infrastructure Engineer) role in CBDS. The successful candidate will
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our AI agents and data-driven workflows — from API integration to cloud architecture and data lake management. We’re building our Enterprise Intelligence Hub and creating AI agents that automate
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interfaces and dashboards within cloud computing environments. To develop and deploy AI-driven modules across cloud and on-premises environments, supporting end-to-end integration, testing, and delivery
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systems. Lead end-to-end delivery of cloud-native, high-availability applications from architecture to production, to guide engineering teams while aligning technology execution with business and research
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Description To design, build, and maintain hybrid scientific data platforms, focusing on backend systems that support both cloud-based and on-premise infrastructures. The role enables secure, human-centred
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Familiarity with ESG (Environmental, Social and Governance) regulations and standards Good written and oral communication skills Proficiency in Python and cloud computing Team player and able to develop
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that is clean, modular, and maintainable. MLOps & Cloud Proficiency: Fluent in the essential MLOps toolkit, including Git, Docker, and CI/CD principles. Have experience building data and model pipelines
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Applications and Cryptography that conducts research into mobile device, cloud, and platform security. Our Education. SCIS has more than 100 students enrolled in the Ph.D. in Information Systems and Ph.D. in
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. Software Engineering Excellence: Demonstrates expert-level Python skills and a strong commitment to Software Engineering best practices, writing code that is clean, modular, and maintainable. MLOps & Cloud