Student Research Assistant Traineeship Programme – Monetary Policy Research/Senior Management/Research Task Force on Artificial Intelligence | The European Central Bank
General Information
Type of contract Traineeship
Who can apply? EU nationals eligible for our traineeship programme
Grant The trainee grant is €1,170 per month plus an accommodation allowance (see further information section)
Working time Full time
Place of work Frankfurt am Main, Germany
Closing date 12.01.2026
Your team
Our research projects and research-based policy analysis use at least one of the following tools:
- Quantitative macroeconomic models
Developing and solving general equilibrium models, including Heterogeneous Agent New Keynesian (HANK) models, to advance our understanding of optimal monetary policy, the transmission of standard and non-standard monetary policy; the interactions between monetary, fiscal and macroprudential policies; macro-financial linkages; and distributional effects.
- Macro-econometric models
Developing existing tools, such as structural vector autoregressions, unobserved components models and non-linear time-series models, to advance our understanding of macroeconomic dynamics, including the impact of monetary policy and financial shocks as well as inflation dynamics and the global financial cycle.
- Micro panel data and cross-sectional data
Analysing granular-level data (e.g. product-level price data, firm balance sheet data, supervisory banking data and new survey data, and household survey data) to gain insights into (i) the transmission of monetary policy via firms and banks, as well as via households’ expectations; (ii) the distributional effects of monetary and macroprudential policies; and (iii) the effects of digitalisation on households and firms.
Your role
- work with datasets, including macroeconomic data and granular firm-, bank- and household-level data;
- work with macroeconomic models, including developing and solving New-Keynesian models, HANK models and models with financial frictions;
- work with macro-econometric models, including developing and estimating structural vector autoregression models and non-linear time-series models;
- work closely with the Division’s economists and research analysts, supporting the team in daily tasks and analytical projects;
- contribute to the Division’s research-based policy advice by using data analysis and econometric and macroeconomic modelling tools to help with empirical and quantitative assessments.
Qualifications, experience and skills
- a bachelor’s degree or higher in economics, statistics, finance, data science, mathematics, engineering or a related field;
- practical knowledge of one or more of the following programming languages: Python, R, Stata or MATLAB;
- knowledge of econometrics (time series econometrics, econometrics of panel data and micro-econometrics), statistics and data science (web scraping, text analysis and other advanced machine learning techniques), and model solution methods (e.g. perturbation methods and global methods);
- a good knowledge of the MS Office package, especially Excel and PowerPoint;
- 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.
- a master’s degree or completion of at least one year of study towards obtaining a PhD degree in economics, statistics, finance, computer science, mathematics, engineering or a related field;
- experience in at least one of the following areas: econometrics (e.g. time series econometrics, econometrics of panel data and micro-econometrics), statistics and data science (e.g. web scraping, text analysis and other advanced machine learning techniques), and model solution methods (e.g. perturbation methods and global methods);
- experience with web-based tools for the LaTeX typesetting system (e.g. overleaf);
- experience of cloud computing (e.g. Amazon AWS);
- experience with supporting research, such as providing data support for research projects or papers;
- experience with one or more of the following: macroeconomic data, firm-level data, accounting data, supervisory banking data, financial market data, other microdata, survey data analysis (e.g. using national surveys, the Eurosystem’s Household Finance and Consumption Survey, the EU Labour Force Survey or others) or large datasets;
- experience using market data services, such as Bloomberg, LSEG Workspace (previously Refinitiv Eikon and/or Datastream), Haver Analytics, SNL Financial, Moody’s Analytics BankFocus (formerly Bureau van Dijk’s Orbis BankFocus) and Moody’s Orbis Europe.
Further information
Application and selection process
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