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Field
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device efficiency. There will be an opportunity to learn the tools required for parallel computing using graphical processing units. This will be used to maximise the computational throughput to enable
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you an engineer who wants to contribute to the high
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for Science @ Scale: Pretraining, instruction tuning, continued pretraining, Mixture-of-Experts; distributed training/inference (FSDP, DeepSpeed, Megatron-LM, tensor/sequence parallelism); scalable evaluation
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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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technical knowledge in areas such as: Foundational Models Algorithmic Research Machine and Deep Learning Computer Vision Edge AI, TinyML, and Embedded AI Explainable AI Safe AI Federated, Parallel
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Deep Learning Computer Vision Edge AI, TinyML, and Embedded AI Explainable AI Safe AI Federated, Parallel & Distributed, Computing/Learning Control Systems Optimization Planning and Scheduling Human
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Education and Experience Preferred Qualifications: PhD in Computer Science, engineering, science, Mathematics, Data Science or similar quantitative subject areas. Expert knowledge of HPC systems, best
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management, program details, communication needs and other details to make events successful. Job Description Primary Duties & Responsibilities: Oversees, manages, and provides assistance as needed for special
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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- Posting may close at any time) Job Summary We are looking for MS and PhD students with experience and interest in state-of-the-art data management technologies, high performance computing, memory management