Liza Darrous obtained her bachelor degree in Bioinformatics from the Lebanese American University. Her bachelor thesis project consisted on working with PLINK SNP data to develop a new combinatorial based logic algorithm for detecting new SNP combinations associated with an increased risk of cardiovascular diseases in a Lebanese cohort.
In 2017, she started her master degree in Molecular Life Science with a Bioinformatics specialisation at UNIL, where she took an interest in statistical biology and thus spent a semester in the Computational Biology Department before joining the Statistical Genetics Group for her master thesis project in 2018.
Following her graduation in 2019, Liza continued in the SGG as a PhD student under the supervision of Zoltán Kutalik. Her thesis, titled “Robust Causal Inference Methods to Assess Risk Factors for Common Diseases”, has encompassed research into Mendelian Randomization methodology and investigating novel approaches to improve its assumption violations.