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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 11 days ago
the context of IPCEI-CIS (Important Project of Common European Interest – Next Generation Cloud Infrastructure and Services) DXP (Data Exchange Platform) project involving Amadeus and three Inria research teams
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increasingly important for autonomy, navigation, inspection, and situational awareness across defence and other safety-critical applications. Yet many real-world deployments cannot depend on cloud computing
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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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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English. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high-performance and cloud computing; (iii
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and corporate offices in Melbourne, China, Indonesia, India and Sri Lanka. Our online Cloud campus provides more than 13,000 students with access to state-of-the-art digital tools and direct access
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their ability to capture movement. Freehand ultrasound offers a radiation-free and flexible alternative but reconstructing and registering sparse 3D point clouds derived from ultrasound data presents significant
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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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scientific datasets. Integrate cloud platforms, high-performance computing resources, and collaborate with infrastructure teams employing MLOps tools for scalable experimentation and deployment. Document and
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable