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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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), transformers, etc. Experiencia entrenando modelos en GPUs. Control de versiones con Git. Manejo de aplicaciones ofimáticas (ver apartado de requisitos específicos). \\ Working knowledge in convolutional neural
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and aerial data. Analysis of large wildlife databases: neural networks. Computing clusters with CPU/GPU. Specific Requirements Educational Requirememts: Machine learning. Signal processing. Signal
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working with climate, weather and earth datasets formats (netcdf, zarr,..) . Working knowledge of High-performance computing (HPC). Experience with GPU-accelerated machine learning frameworks such as RAPIDS
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. Prior exposure to hybrid analog-digital beamforming architectures. 9. Knowledge of FPGA or GPU-based signal-processing platforms. 10. Experience in THz or sub-mm-wave measurement setups
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using
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plus two extra payments of the same amount as the monthly remuneration, or a proportional part for periods of less than one year. 2.5. Tasks to be carried out: · Setup and installation of GPU devices and