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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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detection, avoidance and path planning methods for mobile systems in any field Expertise on object feature detection, classification and localization Real experience on working with different perception
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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innovation, and looking to make a difference. If this sounds like you, you've come to the right place! The successful candidates are expected to perform the following tasks: Conduct research on RF threat
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on retrospective Danish data. The research will include testing different levels of model scaling in terms of data amount and diversity, and training will take place both on a local GPU cluster and on the Gefion
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Finnish National Computing Center (LUMI, Puhti, and Mahti) with thousands of GPUs (A100 and V100) to use (research on large models is available). Help you to produce high-quality research outcomes with
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connections among the different areas. We invite applicants to visit our website to learn more about current research projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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recent architectures such as vision transformer or foundation models Experience in working with subsurface imaging Proficiency in leveraging GPUs and distributed training for large-scale datasets is highly
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for prototyping. Interest and affinity for high-performance computing are necessary for the position. You should have experience with the roofline model and familiarity with a profiler . Experience with GPUs is a