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inference pipelines using modern ML tooling (e.g., PyTorch/TensorFlow/JAX), version control, containers, and HPC/GPU resources. Support the publication of intermediate data products, models, code, and
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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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engineering. The work involves simulations for quantum error correction and mid-circuit operations, and will require both low-level optimization skills (e.g., SIMD, GPU, FPGA) and an understanding of quantum
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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
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. Knowledge of GPU architectures, GPU cloud computing services, and strong familiarity with Linux operating systems. Knowledge of BIM, universal scene description and scene composition Knowledge of physics and
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skills, with the ability to translate complex AI concepts into accessible solutions for diverse stakeholders; (f) possess knowledge of Graphics Processing Units (GPUs) and Neural Processing Units (NPUs
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, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you
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platforms, GPU environments or scientific computing. Experience in EU-funded projects or international collaborations. Experience working with learning management systems or digital learning tools. Knowledge
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fields, applying advanced techniques such as large-scale data processing and GPU-accelerated computing. Access to state-of-the-art research facilities and a new GPU cluster. Collaborative and inclusive