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Field
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interconnects for next-generation AI compute clusters. Information The smart optical networks lab (SONL) at the Electro-Optics Communication (ECO) group at Eindhoven University of Technology is recruiting for a
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work and placements. Collaboration & Networking (10%): Build and maintain collaborative relationships with internal and external partners, build research networks, and coordinate shared projects
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the Nordic region and municipality/industry partners on real use cases for e-health solutions conducting research in software systems, distributed systems, network technologies and advanced data analysis
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The smart optical networks lab (SONL) at the Electro-Optics Communication (ECO) group at Eindhoven University of Technology is recruiting for a PhD position to research novel fast controlled photonic
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, configuration, patching, monitoring, and compliance activities using scripting, configuration management, Infrastructure as Code, and GitOps-aligned practices. Troubleshoot and resolve complex Linux endpoint
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handling and timely escalation of end-user requests and incidents. Provide on-site support for network and communication equipment issues affecting end-user devices, escalating complex infrastructure faults
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integrity standards, including the resolution of complex editorial matters. Contribute to budgeting, forecasting, contract renewals, commercial planning, and other portfolio-management activities. Participate
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uncertainty. This is an opportunity to contribute to the Flexible & Intelligent Complex Systems Research Group through research design, prototype development, simulation-based evaluation, scholarly publication
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, Artificial Intelligence, and Cybersecurity); eleven MS degrees (Computer Science, Health Informatics, Data Science, Cybersecurity, Game Science and Design, Artificial Intelligence, Robotics, Complex Network
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for individuals, organizations or society. You will be part of the SAIL research group, whose research activities focus on AI-based modeling of complex systems, uncertainty management in deep learning, visual