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applying AI/ML models to predict cis-regulatory elements in plant genomes and uncover mechanistic insights into protein-DNA interactions. (2) Developing and applying computational methods to infer gene
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/user behavior, Collect and analyze human performance data (reaction times, workload, situational awareness, eye tracking, etc.), Develop and validate computational models of human behavior in driving
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to develop, implement, and apply novel computational techniques to problems of scientific importance, in collaboration with application scientists and engineers. Topics of interest include data-driven modeling
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engineering (CRISPR/Cas9, Gal4/UAS), including the generation of genetic tools in non-model Drosophila species; single-cell genomics (scRNA-seq and single-cell ATAC-seq); in vivo functional imaging (two-photon
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, and also peripheral nerve stimulation. Responsibilities of the Position Development (design, implementation, and validation) of the proposed IC and system components. Test of the system in animal model
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and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern
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chemistry, battery systems, interfacial electrochemistry, or metallic glass synthesis is desired. The position involves collaboration with theoretical modeling groups and utilization of synchrotron X-ray