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-oriented problems involving optimization, artificial intelligence, workflow redesign, and stochastic assembly line balancing. The position will involve close collaboration with industry partners
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–phenotype–environment interactions. Scaling root traits to agroecosystem processes Ideal candidates will have strong quantitative or computational backgrounds in bioinformatics, breeding, quantitative
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Arabidopsis thaliana. The successful candidate will combine seed physiology, genetics, and transgenic approaches to dissect gene function and regulatory interactions controlling germination decisions
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diverse data sources, including field-collected biological samples, on-farm sensor data, artificial intelligence–derived outputs, and video-based analytics, to support disease surveillance and control. Lead