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-Performance Computing and Future Data Centres AI-Optimized Electronics for Edge and Cloud AI Acceleration – Investigate AI-enhanced data centre electronics, optimizing workload distribution, energy efficiency
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experience Familiarity with core engine technologies such as engine architecture, multi threading, streaming, computer graphics and advanced real-time rendering techniques Experience developing optimized
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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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`Berkeley Lab’s Applied Math and Computational Research Division (AMCR) has an opening in the QuIST (Quantum Information Science and Technology) Group for Project Scientists in support of
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computational methods. Pipeline Development and Optimization: Develop, implement, and maintain statistical, machine learning, and AI pipelines and other informatics pipelines for biomedical data analysis
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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Mathematics, Physics, Computer Science, or Engineering Advanced knowledge of one or more of the following areas: differential geometry, optimization, quantum mechanics, robotics Enthusiasm for applying advanced
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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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reversible CO2 heat pumps. Development and demonstration of an energy optimizing algorithm for reversible CO2 heat pumps (with and without ejector): (i) Use of the previously implemented simulation model