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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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porous materials for CO2 hydrogenation reactions using photo- or thermal catalysis. The successful candidate will be involved in optimizing the synthesis process, with experience in photo-catalysis
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fully automated Prompt calibration which can save tens of person years, millions of CPU hours and speed up the typical CMS analysis cycle times by several years. In addition, it allows better optimization
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skills, expertise, and perspectives necessary to design, conduct, sustain, and disseminate public impact research. We encourage applications from individuals from a broad diversity of PhD-granting
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extended to 2 years. The primary focus of this research will be focused on optimization of multimodal treatment of pancreatic cancer (clinical outcome research). In this role, you will be expected to work
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, industrial energy systems, energy efficiency of manufacturing industry, or other related fields. You will play a crucial role in the planning, execution, and optimization of our technical assistance program
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. Job description Job responsibilities include engineering, transducing, and characterizing primary T cells with synthetic genetic circuits; optimizing and executing protocols for retroviral or lentiviral
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techniques such as cloning, PCR, mutagenesis, DNA extraction, gel electrophoresis 4. Knowledge of protein/antibody discovery and optimization using in vitro display (such as phage or yeast) technology 5
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been shown to accelerate and improve the training procedure of SNNs by defining new cost functions that are differentiable and easier to optimize. They can also handle quantized weights, e.g., using
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data to refine objective measures of neural function and improve clinical strategies for hearing aid optimization in this population. References: [1] A. Starr, T. W. Picton, Y. Sininger, L. J. Hood, and