Stefano Manzini is a molecular biologist turned data-savvy postdoctoral fellow with nine years of hands-on R&D experience across Italy, Germany and Finland, now based in Milan. He combines deep wet-lab expertise (qPCR, NGS/RNAseq, cell culture, biochemical assays) with Python-driven data analysis, image processing and statistical visualization to study drug repurposing and atherosclerosis in animal models. A PhD with multiple publications, he manages both scientific and logistical aspects of EU-funded projects, from experimental design to dissemination and grant writing. His toolset spans pandas, matplotlib/seaborn, scikit-learn and TensorFlow, enabling end-to-end workflows from raw sequencing data to interpretable results. Colleagues rely on him for translating complex molecular assays into reproducible data pipelines, and outside the lab he’s an avid cyclist and kayaker—traits that mirror his methodical, endurance-oriented approach to research.
9 years of coding experience
Ph.D., Translational and Molecular Medicine, Ph.D., Translational and Molecular Medicine at Università di Milano-Bicocca
Picks individual fatty acids from individual complex lipids
Contributions:120 pushes, 1 branch in 1 year 9 months
acidsindividualpickslipids
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