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8 Jul 2026 Job Information Organisation/Company SWINBURNE UNIVERSITY OF TECHNOLOGY Research Field Literature Computer science Researcher Profile Leading Researcher (R4) Application Deadline 20 Jul
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of large, complex datasets. Build and deploy robust ETL processes across on-premises and cloud environments, ensuring reliable, secure and efficient data integration solutions. Collaborate with Integration
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University of New South Wales | Canberra, Australian Capital Territory | Australia | about 2 months ago
, and cloud-native deployment considerations. Demonstrated ability to provide hands-on technical leadership in software engineering environments, including software design, code review, technical problem
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to work across time zones as needed. If you’re excited by cloud engineering, large‑scale scientific computing and the chance to contribute to a major global science mission, this is a great opportunity to
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analysis, or multi-omics integration, with strong competence in deep learning frameworks (e.g., PyTorch/TensorFlow) and data engineering for reproducible research. Familiarity with cloud/HPC workflows
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, team-level priorities. Maintain end-to-end accountability for the reliable delivery of network and telecommunications services across the University's campus, research, and cloud environments. Oversee
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transformation by 2030. Delivered faculty by faculty and aligned with the 2028 Flex-Semester transition for early adopting faculties, it will reshape teaching and learning. The LMS Program goes beyond technology
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. Expertise with AWS CPU and GPU computing, cloud computing, AI model architecture, training, and validation, reinforcement learning, generative artificial intelligence, and data assimilation in an industry and
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. "Studying the origin of the new discovered class of weak CN stars in the Magellanic Clouds using stellar variability" "How do stars merge? Studying the merger between low and intermediate-mass main-sequence
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to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline. User data will remain at the mobile device for ML inference. Problems: In order to enable