Alejandro Navarro is a biostatistics researcher and geneticist with eight years of experience applying molecular and quantitative genetics to plant breeding, currently working at Rijk Zwaan after a PhD and research roles at Wageningen University & Research. He combines strong R programming and statistical analysis skills with bioinformatics, data visualization and a knack for creative problem solving to translate complex genotype–phenotype data into actionable breeding insights. His background spans hands-on lab techniques (CRISPR, DNA cloning, microscopy) to advanced quantitative work on polyploid crops, giving him uncommon fluency across wet-lab and computational domains. Known for clear communication and graphic design sensibility, he excels at making technical results accessible to multidisciplinary teams. Based in Wageningen, he brings both academic rigor and industry-focused delivery to breeding programs.
8 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Genetics, 8.3, Bachelor's degree, Genetics, 8.3 at Universitat Autònoma de Barcelona
Master of Science - MS, Agricultural and Horticultural Plant Breeding, 8.4, Master of Science - MS, Agricultural and Horticultural Plant Breeding, 8.4 at Wageningen University & Research
Repository of SmoothDescent R package. Smooth Descent is a map-cleaning algorithm that can calculate identity by descent probabilities and correct genotyping errors based on marker maps.
Contributions:14 commits, 2 PRs, 56 pushes in 4 months
Contributions:1 PR, 16 pushes, 1 branch in 1 year 10 months
haplotypepolyploidyqtl-mapping
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