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across a range of clinically relevant pathogens. Develop novel computational methods to infer biological function directly from protein sequences, including modeling epistatic interactions and residue
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the interface of machine learning and biology, developing innovative machine learning methods for single-cell data analysis (tools developed by the team: https://github.com/cantinilab). Single-cell high
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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
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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requires a simulator that captures malaria-specific recombination and transmission processes, generating realistic synthetic datasets while retaining sufficient computational eXiciency for large-scale
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physiological function of cellular senescence, and how does it transition from a regenerative program to a driver of pathology? We investigate how senescent cells control tissue plasticity and microenvironmental