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modeling. 80% research - The project focuses on developing theoretical models using optimization and information theory to improve understanding of plant hydraulic regulation at the leaf, plant, and
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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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dynamics (CFD) to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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and optimize molten salt thermophysical property measurements, develop and utilize theoretical models and frameworks to predict salt properties, molten salt thermophysical property database expansion
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, dissemination of research through publications, and mentoring PhD students. The labs’ extensive collaborative networks, both nationally and internationally, span various disciplines, offering diverse applications
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. Implements and optimizes computing workflows using high-performance computing clusters. Prepare manuscripts, abstracts, and presentations, present findings at internal meetings and international conferences
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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the current state of knowledge on specific drugs’ PK and PD properties and on state-of-the-art approaches for study design optimization, dose individualization, and PK/PD modeling and simulation. Frequent