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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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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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) 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
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, including: Cloud infrastructure (AWS/Azure/GCP), Backend systems and APIs for battery telemetry ingestion and analytics, Frontend dashboards for real-time monitoring, diagnostics, and fleet intelligence
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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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. Excellent communication skills and ability to work in a multidisciplinary environment. Familiarity with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC
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: Contribute code in Python (and/or C++/JavaScript), work with APIs, and support cloud-based workflows (Google Cloud/Azure experience is a plus). Documentation and communication: Maintain clear technical
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AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection