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pipelines that will ultimately be deployed onto a cloud-based industry-standard platform, including their subsequent use for further research. This post is full-time (part-time working will be considered, 0.8
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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views in real time. Yet raw video and point-cloud streams are massive, wireless links are unreliable, and safety demands that information be both timely and trustworthy. IONIAN tackles this bottleneck
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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of English and French. Spanish is an asset. - Availability for presential meetings. - Ability to use cloud platforms, websites, Word and Excel. - Excellent organizational, interpersonal, and communication
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to create secure, autonomous and developable solutions that interact with each other and their surroundings, from the edge to the cloud. Project description For this work, you will be working as part of a
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-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular