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  KEYWORD

Machine Learning for Diagnosing SARS/CoV2 from the Analysis of Patients' Exhalations

azienda Thesis in external company    


keywords COVID-19, DEEP LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, SARS/COV2

Reference persons GIOVANNI SQUILLERO

External reference persons Raffaele Correale (NanoTech Analysis S.r.l.)

Research Groups DAUIN - GR-05 - ELECTRONIC CAD & RELIABILITY GROUP - CAD

Thesis type RESEARCH / EXPERIMENTAL

Description NanoTech Analysis is developing innovative nano technologies for performing mass spectrometry. The object of the thesis is the analysis of COVID patients' exhalations, in order to identify appropriate information in the complex mass spectra and correlate the readings to the different cases and specific situations. Preliminary studies are encouraging, and the goal is to build a ML model with a reliability grade (probability of correct identification and data classification) that is acceptable for commercial applications. The candidate will be supported (as needed) by electronic experts, physicians and physicists.

Notes Send a CV to squillero@polito.it


Deadline 31/12/2021      PROPONI LA TUA CANDIDATURA