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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 20 days ago
deployment, · knowledge of GPU computing and large-scale training, · experience working in an HPC environment, · experience with data annotation pipelines or synthetic data generation. We offer: · work in a
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 22 days ago
deployment, · knowledge of GPU computing and large-scale training, · experience working in an HPC environment, · experience with data annotation pipelines or synthetic data generation. We offer: · work in a
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: LightKrylov/LightROM libraries, Incompact3d solver, Pprime CPU/GPU infrastructure, IUSTI experimental database. 4- PRINCIPAL TASKS AND RESPONSIBILITIES ----------------------- a.Stability analyses: Perform
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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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of spikes by a model Develop proxy apps representing the different processing stages of spiking network simulation code (targeting CPU and accelerators such as GPU or IPU) Systematic benchmarking of proxy
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program embedded in a large-scale, nationally funded research consortium with access to unique multimodal clinical datasets - State-of-the-art GPU infrastructure for training and fine-tuning large
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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University invites applications for a full-time, on-site PhD position. The position is funded through the LUMI AI Factory (EuroHPC) and focuses on scalable AI-for-science workflows using GPU-accelerated
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role We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training
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of advanced language models and derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable