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Federico Casale

Machine Learning And Breeding Informatics Analyst at Computomics

Federico Casale is currently a Machine Learning and Breeding Informatics Analyst at Computomics, focusing on genomic and environmental prediction for plant breeding utilizing mixed models, Bayesian inference, and machine learning techniques. Prior experience includes a PhD candidacy at the University of Düsseldorf, where research was conducted at the Institute for Quantitative Genetics and Genomics of Plants, and a role as Graduate Research Assistant at the University of Illinois at Urbana-Champaign, involved in data analysis and laboratory work in the Molecular Weed Science Lab. Additional experience includes positions in grain production and cattle sales, along with earlier roles in genetics teaching and research assistance at the University of Buenos Aires. Federico holds a PhD in Quantitative Genetics and Genomics from the University of Düsseldorf, an M.S. in Plant Genetics from the University of Illinois Urbana-Champaign, and an Engineer's degree in Agronomy and Crop Science from the University of Buenos Aires.

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