Aivett Bilbao is a computational scientist in the . She conducts research on computational tools for mass spectrometry-based omics, working directly with experimental biologists and chemists in interdisciplinary teams. She has acquired extensive experience developing software for mass spectrometry using multiple programming languages and technologies. Projects include proteomics and and small molecule (e.g., metabolites and lipids) molecular characterization entailing both algorithm design and software implementation for data from different instruments (time-of-flight, quadrupole, and Fourier transform-based mass analyzers) and analytical separation techniques (liquid chromatography, ion mobility, solid phase extraction, and gas chromatography).
She earned her PhD from University of Geneva in Switzerland with special interest in data-independent acquisition mass spectrometry. Her bachelor’s degree is in computer engineering from Universidad de Oriente in Venezuela (cum laude) and her MSc studies were focused on machine learning algorithms and statistical methods at Telecom SudParis in France.