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Field
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human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
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focused on food chemistry and the monitorization of oxidative processes and other relevant chemical reactions in food. Supervising and training PhD, master, and bachelor students in analyzing the impact of
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for the construction industry and enable CO2 capture from the atmosphere. Your objectives will include to: Develop new optimization and/or machine-learning based reconstruction and segmentation algorithms to improve
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focuses on the development, synthesis, characterization, and optimization of advanced cathode materials for next-generation Lithium-ion batteries. The successful candidate will contribute to fundamental
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. This position focuses on the design, synthesis, characterization, and optimization of advanced cathode materials for next-generation Na-ion batteries. The successful candidate will contribute to fundamental
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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 RHIC Ion-Ion
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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and PD properties and on state-of-the-art approaches for study design optimization, dose individualization, and PK/PD modeling and simulation. Frequent interactions with PhASR users, including
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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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impact on food security and promote a more sustainable blue bioeconomy. We seek candidates with the following qualifications: To qualify as a Postdoc, the applicant must hold a PhD degree, awarded no