Jon Ahlinder
Scientific Researcher at Skogforsk
Greater Umeå Metropolitan Area Sweden
Summary
👤
Senior🎓
Top SchoolJon Ahlinder is a scientific researcher with nine years of focused experience in statistical and computational genetics, currently applying breeding theory and population genetics to Swedish forest tree species at Skogforsk. His background spans Bayesian inference, phylogenetics, and forensic analysis from a long tenure at FOI, where he developed efficient mixture models for clustering and microbial source-tracking methods. He has a strong academic foundation from a PhD and research roles at the Swedish University of Agricultural Sciences, building Bayesian methods for linear mixed models and meta-regression approaches for macroevolutionary inference. Jon combines theoretical rigor with practical program optimization to improve breeding strategies and genetic data analysis pipelines. Based in the Greater Umeå area, he blends deep statistical modelling skills with domain expertise in forestry and microbial population genetics. An understated strength is his track record of translating complex probabilistic methods into scalable workflows for applied conservation and breeding programs.
9 years of coding experience
12 years of employment as a software developer
Master, Engineering Physics, Master, Engineering Physics at Umeå universitet
Github Skills (6)
solver4
julia3
optimization2
splitting1
numerical-optimization1
operator1
Programming languages (2)
Github contributions (5)
jonhar97/GEM-pop
Oct 2016 - May 2019
Contributions:3 commits, 1 push, 1 branch in 2 years 7 months
jonhar97/Reduced_phenotype_MME
Sep 2022 - Oct 2024
Contributions:14 pushes, 1 branch in 2 years 1 month
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