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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 21 days ago
leverage machine learning techniques to bypass IO bottlenecks in the context of physics simulation on high-performance computing (HPC) clusters. This work is thus placed in a broader ``Machine Learning for
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programming (Python, C++, etc.) and machine learning and signal processing libraries; You have HPC/GPU computing experience, including running deep learning workloads on compute clusters (CUDA-compatible GPUs
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, software, and High Performance Computation (HPC) infrastructure; • Excellent scientific infrastructure; • Participation in project meetings and international conferences; • Flexible working hours
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calculations using all-electron codes (juKKR, FLEUR) on HPC platforms, manage and store data with AiiDA, and extract magnetic interaction parameters for coarse-grained spin models. To replace ad-hoc fitting, we
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The project: The domain of High Performance Computing (HPC) effectively utilises massively multicore computers that facilitate the distribution of scientific workloads across thousands of compute
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The project: The High Performance Computing (HPC) services of today provide the computational density to perform groundbreaking science. These services facilitate the distribution of a problem space
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-generation sequencing analysis is a plus Expertise in AI/ML is a plus Experience with job submission systems/HPC is a plus Proficiency in English (oral and written) Excellent organisational skills and ability
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The High Performance Computing (HPC) research group (led by Prof. Florina M. Ciorba) in the Department of Mathematics and Computer Science at the University of Basel (Switzerland) invites
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working in high‑performance computing (HPC) environments, and prior experience with post-training, fine-tuning, or training large language models (LLMs) is an advantage, but not a requirement. Experience
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. The project has access to the national computing infrustracture, TU/e HPC cluster SPIKE-1 , ASML HPC cluster, ASML datasets, and potentially custom data through collaboration with e.g. IMEC. Where to apply