I am seeking to apply my knowledge in computer science and statistics to understand real world data. I have an interdisciplinary background spanning complex systems, Big Data, machine learning, biostatistics and genomics. I have completed a PhD in which I applied clustering and PCA to epigenomics data and discovered new insights on the coupling between replication and epigenetics. During a postdoral position, I studied the human microbiota during two years at MetaGenoPolis (MGP), an innovative research center. MGP aims at improving human health by developing strategies (eg. nutritional, therapeutical, preventive…) to restore dysbiosed microbiota.
I am currently working in the statistical genetics unit at the Institut Pasteur where I apply my software development and data science skills to quantify the impact of human genome variations on diverse health parameters. My scientific work in the statistical genetic team is anchored around leveraging Genome-Wide Association Study (GWAS) public summary statistics through methodological developments for a better understanding of complex traits (phenotype being affected by numerous genetic variants). I notably developed an imputation method tailored for GWAS Summary statistics (https://gitlab.pasteur.fr/statistical-genetics/raiss). More particularly, I am interested in deciphering pleiotropy (the fact for a variant to impact several phenotypes at once) and extending our methodological developments to diverse populations. To this end, I am managing the JASS project (http://jass.pasteur.fr/index.html) that analyse jointly numerous GWAS datasets to detect new variants missed by univariate analyses.
As a part of my former activities for the hub of bioinformatics and biostatistics, I developed an interest in meta-research (https://research.pasteur.fr/en/project/jobim-2021-pilot-project-gender-speaking-differences-in-academia/). I am specifically interested in the quantification of gender bias participation in scientific activity. To further awareness about equity and diversity in Science, I am member the DEI executive office.
