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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 9 days ago
and domain experts on highly scalable parallel applications with focus on: - development and implementation of parallel aplications, - GPU acceleration of applications, - application optimization
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of visualisation, machine learning / AI, and human-computer interaction Very good programming skills (web-based visualisation, Python, and/or GPU programming) First experiences in the participation in research
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
. The researcher 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
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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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limited to deep learning Experience utilising GPU enabled High-Performance Computing environments is an asset Open minded critical thinker, willing to actively contribute to the further development of multi