As a PhD trainee, you will:

• conduct empirical and theoretical research using state-of-the-art economic and econometric models;
• have the opportunity to submit papers for publication in the ECB’s Working Paper Series and in academic journals.

We are looking for PhD trainees to work on one of the following projects or related projects: 

• developing and estimating asset pricing models (e.g. yield curve models), including models for risk-free rates, sovereign bond yields and market-based inflation compensation, possibly featuring a macro-finance nexus;
• assessing financial conditions for firms, using firm-level financial and survey data (e.g. data from the Survey on the Access to Finance of Enterprises in the euro area, financial statements and corporate bond data);  
• developing and estimating structural macroeconomic models featuring, for instance, heterogeneity, financial frictions, deviations from rational expectations and/or non-linear propagation;
• conducting empirical analysis on the impact of monetary policy (e.g. using high-frequency identification), focusing especially on non-linearities and granular data.

Essential: 

• a master’s degree and at least two years of PhD studies in the field of economics, finance, statistics or data science, or a related field;
• a sound understanding of, and a theoretical background in, macroeconomics or finance, and the economic and institutional context in which the ECB fulfils its mandate;
• excellent knowledge of, and a track record in, state-of-the-art modelling tools and econometric techniques or data analytics;
• programming skills in one or more of the following software packages: MATLAB, Stata, Python, R and Julia;
• a good knowledge of the MS Office package;
• an advanced (C1) command of English and an intermediate (B1) command of at least one other official language of the EU, according to the Common European Framework of Reference for Languages.

Desired: 

• experience of working with one of the following: macrodata and macroeconometric methods and models, non-linear solution methods, microdata and microeconometric methods and models, non-linear time series models and machine learning techniques.