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population sampling expeditions, genotyping of collected specimens using high throughput sequencing and associated lab work, analysis of large-scale genomics data, phenotypes of collected plant specimens in
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data science, artificial intelligence, large language models, and high-performance computing. Strong written and verbal communication skills regarding research results. Preferred Qualifications
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visualization, geospatial analysis, and processing of large amounts of meteorological and remote sensing data. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a
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. Develops and applies numerical and statistical models to better understand and predict flood risks in coastal environments, including the integration of hydrodynamic, climatic, and socio-environmental data