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of their career developing state-of-the-art statistical and mathematical methods to analyze epidemic data, with the aim to increase our understanding of how pathogens spread in populations, assess the impact of
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ear gene therapy. The characterization of gene regulatory elements and gene regulatory networks is essential for this purpose. The candidate will use computational methods to develop and integrate novel
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. Responsibilities will include: Developing expertise in audiological test batteries Data wrangling, cleaning, and feature engineering Applying and implementing statistical or machine learning methods, depending
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polysaccharide of the C. albicans CW, links the internal and external components of the CW (see our article, PMID: 39636210). Despite being a critical constituent of the CW, the biosynthesis and remodelling
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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organismal properties encoded in the interplay of multiple genes in a network? How does the polymer physics at the level of the DNA affect the identity of a particular cell type? Alternative questions
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods
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-phenotyping of individuals with autism and controls including brain imaging (EEG and MRI) and a battery of cognitive tests. Our group is currently developing new methods for analyzing whole genome and brain