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, diverse, and multi-institutional team, including experimentalists, design engineers, and computational scientists, on the design and optimization of tritium breeding blankets and fusion reactor cooling
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species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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, optimize, and test advanced materials that will accelerate the deployment of higher performance nuclear energy systems. As part of our research team, you will evaluate accelerated testing methods (in-situ
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including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command
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engineering or equivalent field and 0-2 years of research experience. Background in quantitative analysis, mathematical modeling, data science and simulation techniques with expertise in optimization techniques
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companies participating in the DOE’s Better Plants program. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service