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-truth data collection, and operating, testing, validating, and refining crop models to improve prediction accuracy. The candidate will also contribute to the development and application of machine
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compliance (5%). •Conduct research on artificial intelligence (AI) and machine learning (ML) to analyze large-scale biological, genomic, metabolomic, and phenotypic dataset (25%). •Investigate the genetic
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-validation by droplet digital and real-time PCR. Contribute to the host–microbiome analyses (GWAS/mGWAS, metagenomics) and the integrative modeling led by the graduate student. Apply machine-learning and AI
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other computer related tasks, such as Microsoft Office. Preferred Special Knowledge, Skills and Abilities: -ImageJ and Matlab. -Expertise in biosensors or protein design. -Familiarity with genetic model
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