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Field
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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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expressions for latency and offloading probabilities across edge-only, cloud-only, and edge-cloud computation offloading algorithms. Design and develop robust Python APIs for edge-only, cloud-only, and edge
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to improve cloud scheme that contributes one of the most important uncertainties in climate projections (Wang et al 2026, Nature Communications). Wang et al (2026) found that climate models largely
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. What you would be doing: Support and develop data pipelines for My Heart Counts smartphone app data and integrate with biological (omics), clinical and environmental datasets; manage cloud resources
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data pipelines for My Heart Counts smartphone app data and integrate with biological (omics), clinical and environmental datasets; manage cloud resources (Google Cloud) and ensure data integrity and
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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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papers in peer-reviewed Journals are key to the role. You will be responsible for: Design and implement full stack battery intelligence platforms, including: Cloud infrastructure (AWS/Azure/GCP), Backend
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Engineering, Computer Science, or a related field. Proven experience working with wireless sensors, point cloud data processing, and sensor integration. Strong background in signal processing, computer vision
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to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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) Experience working across the XR system stack, including lower-level components such as sensing, networking, systems optimization, or edge/cloud integration Experience incorporating machine learning