Trade network analysis

1 Research Collaborator position
(Deadline July 7th, 2022 13:00 )

Trade Network, econometrics, complex networks, machine learning


The IMT School aims to recruit an expert in international economics, econometrics, complex networks and machine learning with particular reference to the empirical analysis of international trade flows and business microdata. The ideal candidate has mastered econometric analysis and machine learning techniques and has a doctorate in economics, management, or related subjects. The research will be conducted within the Axes research unit and contribute to the definition of new predictive models and causal analysis of international trade.


The selected candidate will analyze international trade data, with particular emphasis on using data at the product and company level and company balance sheet, to contribute to the definition of predictive models of future business dynamics and the study of the causal impact of shocks and changes in economic policies. The researcher will use econometric techniques, machine learning, and complex network analysis, with particular emphasis on the use of methodologies to identify causal effects and their possible heterogeneity linked to products, business and network characteristics. The analysis will be carried out on databases available at the Axes research unit and in collaboration with the researchers of other research units at IMT School for Advanced Studies, Lucca.

Formal requirements
  • PhD in economics, management or related subjects;
  • Knowledge of the English language, both written and spoken.


Specific requirements
  • Knowledge of international trade theories;
  • Knowledge of econometric and machine learning techniques;
  • Knowledge of complex network analysis techniques;
  • Previous experience in the analysis of foreign trade and business data through the use of Stata, R or Python applications.

1 year

Gross amount

 € 20.265,00/year


SECS-P/06 Economia Applicata


“Network analysis of economic and financial resilience- NAEFR”- CUP D67G22000130001 - P0245

Job Research Area: 
Job Research Unit: 
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Assegno di ricerca


Apply ONLINE only.

Before filling in the application form, please read thoroughly the full call and collect all the files you may need:


  • Personal info and contact info (compulsory);
  • University degree (compulsory);
  • PhD (compulsory only if stated in the full call).


  • The scanned copy of a valid identity document (Passport or Identity Card - compulsory);
  • Your CV in English (compulsory).