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intelligence models (LLMs) in multi-GPU environments. Preparation of technical documentation, best practices for development and operation. Where to apply Website https://sede.uvigo.gal/public/catalog-detail
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(AWS, Azure/GCP) Experience in open source software development. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques will be valued. Fluency in spoken and written
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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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including knowledge of PyTorch, Tensorflow, Pandas, Scikit-learn and/or Numpy. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques. Fluency in spoken and written
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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