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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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join our research activities focused on the development and long-term durability of SOEC cells, with particular emphasis on operation under technologically relevant conditions. Electrolysis and green
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by real-world challenges arising across different application domains. The research focuses on strengthening product/production development processes, and decision-making in complex engineering systems
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Description Electromagnetic techniques can provide a means for rapidly analyzing or processing biochemical samples in a manner that can be readily scaled up to handle large numbers of samples in massively
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on competence: contributing to research software development supporting simulations and/or data workflows (HPC/parallel environments), and open/reproducible release of data and analysis scripts under FAIR
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systems based on massively parallel hardware architectures Combination of programmable logic, tensor processors and general-purpose CPUs for real-time adaption and scheduling services (e.g., AMD Versal
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algorithms will be assessed for neurodegeneration mapping in Alzheimer’s disease brain organoids. In parallel, the technology and algorithms will be applied to fish health research, supporting studies on ulcer
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dedicated to improving quality of life across the world. This position will play a crucial role in ensuring the continuous operation and enhancement of our High-Performance Computing infrastructure
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dedicated to an ethic of civil and free inquiry, which respects the autonomy of each member, supports individual capacities for growth and tolerates differences in opinion; treat all faculty, staff and
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, the system and associated algorithms will be assessed for neurodegeneration mapping in Alzheimer’s disease brain organoids. In parallel, the technology and algorithms will be applied to fish health research