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Field
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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platforms and our local CPU and GPU clusters; implementing Python tools for automating CSP/DFT calculations; - Participation in the scientific activities of the Applied Quantum Chemistry group (IC2MP) and the
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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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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 13 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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of cores, and a growing GPU cluster containing thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance
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. Qualifications: Familiarity with machine learning interatomic potentials, CPU and GPU parallelization, knowledge of LAMMPS and molecular dynamics, experience with first principles calculations of dielectric and
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on small test clusters. Test computational performance and resolve technical challenges on significantly larger models of selected quantum materials. Work on speeding up Krylov solvers on GPUs. Demonstrate
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Experience with HPC (GPUs preferred) Related Skills and Other Requirements Ability to work at the interface of AI and science/engineering problems Ability to lead, develop, and contribute to multiple projects
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, engineering, physical science or related technical discipline. Experience: Expertise in developing and training AI models Proficiency in Python Experience with HPC (GPUs preferred) Related Skills and Other
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 16 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