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- Simulación en entornos virtuales para el estudio de algoritmos de clasificación de objetos y generación de datasets ------------------ - Implementation of algorithms in embedded processing systems for train
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The Brainlab – Cognitive Neuroscience Research Group (Universitat de Barcelona ) is seeking an outstanding candidate with strong motivation for the neuroscience of music and its impact on early development
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networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm development, hardware/software
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-------------------------------- - Implementation of algorithms in embedded processing systems, train integrity algorithms in IoT - Programming of embedded systems and HW implementation for IoT in railway applications Where to apply E-mail
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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site-specific and realistic radio propagation data through GPU-accelerated ray tracing to train AI/ML algorithms. Exploring the use of generative models for wireless channel modeling, e.g., to produce
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: Neural networks and machine learning. Algorithm. Professional Experience: In the use of Python (PyTorch, TensorFlow) and C for the development and optimization of deep learning algorithms. Experience in
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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for cooperation and social responsibility, contributing to the sustainable development of the region and to the critical and engaged education of new generations. ViCOROB is a research institute at the
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. This work seeks to develop and apply novel technologies based on compact data structures for handling, among other, genomic datasets in large-scale comparative genomic analyses. Compact data structures