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edge AI hardware/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a
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/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a scenario generator for
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and session/stream/track organizer of major scientific conferences, such as IFORS 2026, EURO, TRISTAN XI, Odysseus, and the Aussois Workshop on Scheduling. Beyond academia, she has extensive industrial
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Max Planck Computing and Data Facility (MPCDF), Garching | Garching an der Alz, Bayern | Germany | 2 months ago
, including tools for remote access, job scheduling, and performance profiling Proven experience in handling large-scale, multi-dimensional datasets Strong background in prototyping and optimizing ML/AI
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freedom and provide significant potential for increasing the efficiency in today’s train schedules. While this certainly provides a great deal of freedom and potential for improvements, utilizing