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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 and green AI. Use cases in
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of GPUs and/or time in either training or inference procedures, which pose considerable challenges to both academia and industry for widespread access and deployment. In particular, the sampling process of
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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nature of electroweak symmetry breaking and mass generation in the standard model. We developed state of the art (open source) software working on GPU- and CPU-based supercomputing architectures, and
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. The Center has state of the art equipment within DNA and RNA sequencing, laboratory automation, CPU and GPU compute resources, proteomics, metabolomics, and advanced microscopy. This position offers
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-scale training of a high-performance foundation model using a dedicated GPU cluster Fine-tuning the pretrained model on real-world health data from lifespin’s proprietary database Collaborating closely
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physics, 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
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equivalent degree in physics, 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
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Good knowledge of AI and applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience