Samuel Le Meur-diebolt is a research-focused bioinformatics engineer and neuroscientist with 11 years of hands-on experience developing statistical pipelines and imaging tools for functional ultrasound and proteomics. Trained at ESPCI Paris and MINES ParisTech and currently a Research Fellow at UCL, he bridges academic research and industry practice, having implemented GWAS and mendelian randomization workflows at Sanofi and advanced fUS registration, analysis, and web apps in neuroimaging labs. He combines strong coding across R, Python, MATLAB and system administration with practical experience in 3D fUS imaging for pharmacological studies, reflecting a knack for shipping reproducible, open research tools. Notably, his background spans mass spectrometry algorithm development to building Spark/tabix-based databases, revealing an unusual breadth from low-level algorithmics to scalable data engineering.
Contributions:54 pushes, 1 branch in 4 years 3 months
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