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Field
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images against reference pre-training and post-training workloads together with Apertus engineers, and maintain working launch examples Compute partnership and efficiency Serve as the primary technical
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. Documenting system administration procedures for routine and complex tasks. Technical Environment: Linux build automation in a large, distributed computing environment with Puppet/Ansible/Git/Docker; scripting
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. Working knowledge of coding in a distributed computing environment, including basic familiarity with parallel processing concepts and research workflows that use distributed or multi-node computing
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-throughput processing. Enhance the computational efficiency of compute environments by optimizing resource allocation (including CPU/GPU utilization), parallelizing data pipelines, and resolving processing
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Intelligence, Machine Learning, Data Science, Security and Privacy, Parallel and Distributed Computing, Deep Learning, Internet of Things (IoT), and Algorithms. Successful candidates will hold a joint
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software in high-performance computing (HPC) environments. Experience with parallel and accelerated computing frameworks (e.g., OpenMP, MPI) and familiarity with GPUs and large-scale storage systems. Strong
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function as a coherent programme rather than as parallel projects. Day to day, you will chair consortium meetings, facilitate the weekly, biweekly and monthly catch-up meetings between all cohorts
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emphasis will be placed on obtaining particles with controlled size distribution and morphology that enable good and reproducible electrolyte performance. In parallel, industrial aspects such as solvent
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environments, work on real problems with external partners, and undertake substantial workplace learning through the Integrated Work Study Programme. Our approach to education is explicitly competency-based
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80%-100%, Lugano, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in