Data Analytics in Socio Technical Systems: The evolution of scientific, technological and industrial clusters
The research project aims at developing and implementing new methodologies in the analysis of scientific, technological and industrial networks utilizing a wide range of methodologies and approaches (network science approaches, natural language processing/machine learning approaches, econometrics, ...).
The research program consists in the integration of data from heterogeneous sources, also with the aim of developing composite indicators of competitiveness of different geographical clusters, with particular reference to the life sciences.
The ideal candidate should be comfortable working with large scale databases (utilizing also cloud resources such as Google BigQuery), web APIs, and should have previous experience working with programming languages such as Python, R, or Julia. Previous experience in econometrics and machine learning is highly appreciated.
The project is a joint collaboration between the Polytechnic University of Milan, the Centre for Analysis, Decision, and Society (Human Technopole), and the laboratory for the modeling of biological and socio-technical systems (MOBS Lab, Northeastern University).
The duration of the appointment is one year and it is renewable for up to 5 years.
|Lab||Polytechnic University of Milan, MOBS Lab (Northeastern University), CADS (Human Technopole, IT)|
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