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Good knowledge of AI and applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience
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education in theory and practice of generative modeling, have research experience or education in life science data and have prior experience with remote GPU and HPC services. After the qualification
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communications. Evaluation of model performance can be conducted based on the data collected through the water tank. We have the GPU machines ($14k) to develop deep neural networks for underwater communications
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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calculated using our Software Energy Lab, which has multiple test machines with GPUs and, in the future, AI accelerators. Development teams currently lack guidance on how to create sustainable systems. You
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us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
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equipped with 8 GPUs. This infrastructure will enable the efficient training and evaluation of complex neural network models, essential for the project's success. The significance of this project for our