As a researcher, I develop computational methods to better understand the risks associated with environmental factors such as nutrition and chemical pollutants. These methods include machine learning models, multiomic & scRNAseq data analysis and the development of New Approach Methodologies (NAMs) and interactive tools to explore chemical hazards.
As a consultant, I bring expertise in data science, biology and toxicology to scientists and industry. With my mixed background I can provide insightful data visualizations and deep interpretations of the underlying biological significance.
Disciplines: Data Science, Bioinformatics/Biostatistics, (eco-)Toxicology, Biology, Computational Biology, (Neuro-)Endocrinology, Neuroscience, Chemo-informatics.
Expertise Keywords: Multiomics, Endocrine Disruption, In Silico methods, Adverse outcome pathways (AOPs), scRNAseq, Transcriptomics, Metabolimics/Lipidomics, HPC, Git, Shiny, Machine Learning, Linux, Bash.