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candidate will be able to influence the direction of the project depending on his/her profile and strengths (including adding a small experimental component). The position is funded by the ANR. The monthly
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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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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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methods to decipher the transformation of sounds both at the peripheral and central levels. Project summary The aim of this project is to study how information about sound frequency or intensity
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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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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