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data and simulations to understand the physics driving enrichment technology and identify optimization paths. Independently complete research to advance high mass ion source technology for flexibility
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coding (Python) for building energy modeling and controls Preferred Qualifications: Expertise in modern optimal control techniques (e.g., AI based controls) High level of competence in coding and scripting
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). The Emerging Technology Computational Group facilitates ORNL goals through HPC systems engineering, integration, and support for the research community at ORNL. By providing design, deployment, optimization
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control methods to optimize pellet-fueled plasma scenarios. These studies will primarily be conducted on the Wendelstein 7-X stellarator located in Greifswald, Germany. This position is located at Oak Ridge
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. Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification. Collaborate with AI/ML experts to design and test inference methods that map
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that integrate with existing or new large language models and large vision models for resource optimization with energy grid data. Provide coding support to implement privacy preserving federated learning
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research analysis on geothermal well development and other advanced energy technologies that could achieve transformative gains in energy efficiency. Ability to develop optimization and life cycle models
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methods, complex optimization, population and evolutionary dynamics, cyber security and power grid analysis, and uncertainty quantification for engineered systems. Collaboration with experts from various
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understanding of machine learning methodologies and data science methodologies and techniques, (e.g. supervised and unsupervised learning, feature selection/engineering, hyperparameter optimization
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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