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using clusters like UPPMAX and GPUs for high-performance computing and parallel computing using clusters like UPPMAX and GPUs for high-performance computing are essential. While not required, experience
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, immersive, and interactive technologies. Highly proficient in real-time engines, AI-assisted tools, GPU-accelerated platforms, and emerging computational design workflows, you combine creativity with
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The Computer Science program in the Computer, Electrical and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa ) at King Abdullah University of Science and Technology (KAUST
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
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research profile, and an international network around big data in marine sciences. The candidate will have access to NIOZ’s high-performance computing cluster, GPU nodes for deep learning, dedicated data
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that outperforms highly optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance
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dynamics simulations using parallel computers or GPU computers. We correlate the obtained results with experimental data on polymeric functional materials to elucidate their dynamic behavior and clarify
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Microscopy Center. The project further benefits from excellent dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. This is a full-time, two-year
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dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. You will receive extensive training in these techniques as part of your PhD project and will work