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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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roles or positions in industry. A supportive and collaborative team committed to fostering your growth as a researcher. What You’ll Do Process calcium imaging data using GPU-based software packages
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GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer vision challenges) Experience with version control (Git) and collaborative development practices
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modules, and monitor training progress. Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time. System Integration Work with the research team to connect AI
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the necessary algorithms. You will also develop and document a graphical user interface which handles large processing tasks efficiently and uses multiprocessing and GPU acceleration where necessary. At the same
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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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programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
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Position Summary: The Research Engineer will be responsible for the smooth operation of the VIDAR Lab hardware and software stacks, including GPU clusters and related computing resources. This position will
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to