Summary
Marc Weber is a Bioinformatics Lead based in Barcelona with a decade of industry-focused experience and over 15 years in research combining physics, computational biology and mathematical modelling. He builds end-to-end analysis pipelines and quantitative models of protein synthesis and gene regulation, integrating diverse omics (ribosome profiling, RNA-seq, proteomics, tRNA-seq) and machine learning like random forest regressors. Formerly a CRG postdoc, he led collaborative projects, supervised students, taught whole-cell modelling workshops, and published multiple first-author papers that bridge experimental and computational teams. Now leading bioinformatics at Flomics, he brings a rare blend of hands-on C++ simulation and Python data-visualization skills plus practical experience translating stochastic and systems-level models into actionable biotech insights. An oft-overlooked strength is his background in high-performance and parallel computing from early Monte‑Carlo and supercomputing work, which underpins his ability to scale analyses for large genomic datasets.
10 years of coding experience
10 years of employment as a software developer
Master Physics, Master Physics at EPFL
Ph.D. Physics, Ph.D. Physics at Universitat de Barcelona
English, French, Spanish, Catalan, German