-
work with Prof. M. Ángeles Serrano and Prof. Marián Boguñá at the interface between Network Science and Machine Learning. The goal is to merge the best of the two worlds to produce a new generation of
-
federated learning approaches and models for diagnostic pathway support and risk score prediction in cardiology using real-world data. We are offering at the University of Barcelona, within the Artificial
-
) solutions to provide access to antenatal screenings in developing countries, where access to data and specialists is often not possible. Moreover, integrative-adaptive learning methods will be implemented
-
surveys, and modelling of infrared data will be regarded as a plus, as well as the motivation to learn new skills and work independently. Social security and public healthcare benefits, covering spouse and
-
to team work, high reliability, attention to detail, eagerness to learn, pro-active and responsible attitude, intellectual independence; Excellent command of English. The two writing samples (articles
-
programming Expertise in additional quantitative research methods (e.g. time-use analysis, system dynamics, machine learning, econometrics, advanced statistics, big data, material flows analysis, etc
-
related to modelling (e.g. integrated assessment models, stock–flow consistent models, system dynamics, input–output analysis, econometrics, machine learning, material/energy flow analysis, etc.) Motivation
-
of infrared data will be regarded as a plus, as well as the motivation to learn new skills and work independently. Social security and public healthcare benefits, covering spouse and children. A generous