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generate massive phenotypic datasets. We will analyze these data using deep learning to identify novel antibiotic candidates and predict their mechanisms of action. This pipeline will allow us to explore new
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, interdisciplinary group engaged in civil, electrical and mechanical engineering, driving forward innovative research and solutions. It also has an internationally leading profile in computational science and
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, are discriminant). In particular, point i) undermines most of the recent deep learning machinery used for shapes classification [e.g. PointNet Qi et al., 2017], even if one wished to adopt them for simple feature
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, which performs numerical analytics during the simulation. This is necessary due to the ever-growing gap between file system bandwidth and compute capacities. To this end, we are developing the Deisa
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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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mechanisms that could constitute relevant targets for new treatments. We are leading the genetic work package of AIMS-2-TRIALS, the largest European project on autism research. The project is focused on deep