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or quasi-mechanistic models Multi-Agent AI Systems for Scientific Discovery: Pioneer the development of multi-agent computational systems where specialized AI agents collaborate to solve complex genomic
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for a postdoctoral position in the group of Prof. William Glover at NYU Shanghai. A range of projects are available related to the excited-state dynamics of complex systems, including: (i) developing
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of quantitative, experimental, and clinical scientists. ● Present complex results clearly and concisely to diverse audiences. Who You Are ● You have a Ph.D. in Computational Biology, Bioinformatics, or a related
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supervision Have proven ability to use sophisticated econometric tools to analyze complex financial data on a large scale Be able to conduct research and write research papers/reports in both English and
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. The insights gained from this well-controlled model will provide a foundation for understanding analogous processes in more complex human cellular systems. The research aims to establish mechanistic
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vehicles navigating shared road networks, AI agents coordinating in complex games, and human-machine partnerships in online platforms, AI assistants, and physical systems. While multi-agent interactions have
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domains. Hopper Fellows concentrate on the development and optimization of scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run
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, genomics, and other scientific domains. Hopper Fellows concentrate on the development and optimization of scientific and engineering applications leveraging high-speed network capability provided by
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and effectively communicate about complex bioinformatics problems to both technical and non-technical audiences; this should be both in written and verbal form, as evidenced by first-author publications
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solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis, integration