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). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
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range of molecular systems, including: Transition-metal complexes (e.g., chiral ruthenium and iridium complexes) Local and nonlocal inner-shell decay processes in solvated ions and transition-metal
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protein allowable milk with the least amount of feed and animal inputs under feeding and management conditions in India. • Integrate the feed chemistry data being developed in a parallel project. • Travel
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research
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testing experimental Forecast-Informed Reservoir Operation in the Hydrometeorology Research Group. In accordance with USCIS regulations, successful applicants must be legally able to accept work in the
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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative
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parallel testing facilities for companion dogs and children, including equipment for eye-tracking, thermal imaging, touch screen studies, behavioral analysis from video. There is also the possibility
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testing experimental Forecast-Informed Reservoir Operation in the Hydrometeorology Research Group. Benefits at UTA We are proud to offer a comprehensive benefits package to all our employees
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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productivity while reducing external inputs. In parallel, the lab is expanding efforts to understand microbiome-associated phenotypes that contribute to drought tolerance and soil water retention. This includes