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Field
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Systems and contribute research in areas such as distributed systems, cloud and edge computing, high-performance and parallel computing, large-scale data processing, resource management and scheduling
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and parallelization of scientific simulation codes. In research in theoretical or computational quantum physics. In the development and application of Quantum Monte Carlo methods. Having worked
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of the group. Strong knowledge of performance modeling, simulation, and benchmarking of parallel and distributed computing systems and of the workflow systems that run on them. Familiarity with the FAIR data and
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dependencies for execution on Alps / CSCS infrastructure. Run and monitor Slurm-based training and evaluation jobs. Debug failures related to distributed execution, checkpointing, filesystem performance
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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in
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administration (OpenHPC, Redhat Enterprise 7/8, CentOS 7/8/Stream, Ubuntu), experience with SELinux is a plus Parallel and distributed file system (Lustre) experience is a plus, as well as knowledge of Ceph
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? No Offer Description The researcher’s scientific activity will be carried out within one or more of the following areas: Computer Architectures; Databases; Parallel Computing and High-Performance
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and Product Development, where multiple externally funded research projects are conducted in parallel in close collaboration with industry, public authorities, and international partners.The successful
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of vector query processing, serverless/just-in-time query execution, parallel and distributed data management, and data management systems on emerging hardware Passionate about inventing, building, and
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dynamic technological environment. Preferred Qualifications: Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g