Vanessa De Melo is a Data Scientist and biologist with 11 years of research experience translating transcriptomics and metabolomics datasets into actionable biological insights. With a PhD in Evolutionary Biology, she combines hands-on molecular lab work and high-performance computing to build reproducible RNA-seq, ChIP-seq and untargeted metabolomics pipelines in R, Python and Bash. Her work at Eawag uncovered metabolic and gene-expression adaptations to temperature and nutrient shifts in phytoplankton, and she has optimized data-processing workflows to accelerate daily experimental decision-making. A clear communicator and mentor, she routinely supervises students and collaborates across interdisciplinary teams to turn complex omics data into publishable stories. Uncommonly for a biologist, she pairs ecological intuition with software engineering practices to deploy analyses on national supercomputing infrastructure.
11 years of coding experience
5 years of employment as a software developer
Master's degree, Ecology and Evolution, Master's degree, Ecology and Evolution at University of Bern
Doctor of Philosophy - PhD, Evolutionary Biology, Doctor of Philosophy - PhD, Evolutionary Biology at University of Zurich
Bachelor's degree, Biology, Bachelor's degree, Biology at Universidade Federal de Santa Maria
Exchange Student, Exchange Student at Free University of Bozen-Bolzano
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