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Field
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) Distributed Systems and Networking. These key research areas have a special thematic focus on (a) Health Informatics and (b) Security and Privacy-aware Computing related applications. The initial appointment
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) Distributed Systems and Networking. These key research areas have a special thematic focus on (a) Health Informatics and (b) Security and Privacy-aware Computing related applications. The initial appointment
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to quality, integrity, creativity and cooperation. You have strong interest in communication networks, distributed systems, or cloud/edge computing. You have at least basic programming skills (e.g., Python, C
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LevelPhD or equivalent Skills/Qualifications Who you are You have a PhD, preferable in Computer Science, Engineering, Mathematics, or equivalent. You have a strong background with parallel and distributed
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10 Mar 2026 Job Information Organisation/Company Sorbonne University Department LIP6 Research Field Computer science » Other Engineering » Electrical engineering Physics » Optics Researcher Profile
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distributed computational pipelines and optimizing communication costs. You will also contribute to the integration and testing of the models in real D-MIMO environments, in close collaboration with a PhD
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 2 days ago
funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD project is part of
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-compliant data infrastructures that enable secure data sharing, reuse, and AI-driven analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical
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existing and creating new deep learning-based models for anomaly detection, theoretical and numerical studies of detection quality, creating new distributed computational pipelines and optimizing
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contract is based on § 2 WissZeitVG. Your Tasks: Generative diffusion models (DMs) learn to reverse a diffusion process from an analytically known prior distribution to a target distribution that is inferred