We welcome Leonardo Fedrigotti, Martina Barbagallo and Davide crucitti, who will start their master thesis on chemometrics related topics. In particular, Martina will develop and validate proper chemometrics strategies based on advanced neural networks and deep-learning models to predict the molecular structure of some substances starting from their LC-MS/MS spectra, which were previously organized in a database. Davide will work in the field of QSAR, developing a model to classify substrates, inhibitors and non-active compounds of P-Glycoprotein using artificial neural networks. His project will be carried out at the Slovenian National Institute of Chemistry. Leonardo will develop a model which is able to couple GC-MS data and features of encephalographic responses (EEG) measured with portable low-cost devices to assess odor-stimulated emotions and to ensure scientific measurements of such signals. Coupling and comparison of analytical sources will be carried out through chemometrics methods. This project will be carried out at P&G (Bruxelles).