General Information
Type of contract
PhD traineeship
Who can apply?
EU nationals eligible for our traineeship programme
Grant
The trainee grant is €2,120 per month plus an accommodation allowance (see further information section)
Working time
Full time
Place of work
Frankfurt am Main, Germany
Closing date
23.08.2021
Your team
You will be part of the Stress-Test Modelling Division in the Directorate General Macroprudential Policy and Financial Stability. Our Division has around 30 members of staff and is responsible for: (i) developing and maintaining the ECB models used to perform stress-test exercises, with a focus on stress tests for macroprudential purposes; (ii) supporting the microprudential stress-testing activities of the ECB and the European supervisory authorities by providing scenarios and advanced analytical input; (iii) helping to assess systemic risks in the context of the preparation of the Financial Stability Review; (iv) supporting the activities of the wider Directorate General by providing quantitative models that can be used to assess the potential impact of systemic risks on the stability of the euro area/EU financial system and to calibrate macroprudential measures; and (v) contributing to European and international discussions on the resilience of the financial sector, in particular by contributing to ECB publications and providing relevant analytical support to the European Systemic Risk Board.
A recently acquired additional responsibility of the Division relates to its involvement in the ECB’s new workstream on climate risk in the context of which we are developing and following a stress-test approach to assess the financial stability implications of climate risks. The climate risk stress test entails the model-based design of long-horizon macroeconomic-climate scenarios. The mapping of climate-related financial risks is conducted using microeconometric models exploiting a number of firm-level and loan-level granular databases available internally.
In your role as a PhD trainee, you will be part of one of the teams into which the Division is organised, each being responsible for policy-relevant analysis and model development for some of the specific tasks outlined above.
The ECB is an inclusive employer and we strive to reflect the diversity of the population we serve. We encourage you to apply irrespective of age, disability, ethnicity, gender, gender identity, race, religious beliefs, sexual orientation or other characteristics.
Your role
As a PhD trainee, you will contribute to the development of models for the assessment of financial stability risks (also climate-related ones) and the impact of macroprudential instruments (both capital-based and borrower-based) using methods such as structural and Bayesian VARs, panel regressions and other microeconometric approaches, integrated micro-macro frameworks, as well as DSGE and network models. This might also include working on the infrastructure of the stress-test models.
The position offers excellent opportunities to become familiar with the area of macroprudential policy and financial stability through different tasks and projects. You will be able to develop your potential and gain an overview of all the activities performed by the Directorate General, and may also contribute to its regular work. You will have your own assigned supervisor, but will be expected to use your own initiative and work in a largely autonomous way in order to complete your projects.
You will be able to attend a wide range of seminars and will have access to the ECB’s library, as well as computing, programming and statistical resources. You will have an excellent opportunity to network, engage with other employees and increase your personal awareness and business knowledge. You will be part of a multicultural team that strives for continuous innovation to make a positive impact on the lives of European citizens.
Qualifications, experience and skills
Essential:
- a master’s degree and at least two years of PhD studies in finance, economics, statistics, mathematics, physics, engineering, computer science or a related field;
- a solid background in one or more of the following fields: macroeconometrics (including Bayesian VARs), financial instruments, institutions and markets, panel data econometrics and other microeconometric techniques, DSGE models, numerical techniques, mathematical optimisation models, computational economics, network analysis, banking theory, monetary economics and/or corporate finance;
- an advanced knowledge of programming languages and econometric software (e.g. Python, R, MATLAB, C++, Stata, SQL and/or EViews);
- 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 in working with large granular datasets, combining different data sources and drawing information from complex financial and real sector data;
- a good knowledge of at least one of the areas described under “Your role” above.
You are curious and eager to learn, and want to further develop your ability to analyse complex information. You are keen to collaborate with others, pursue team goals and learn from other people’s diverse perspectives. You strive to know and anticipate stakeholder needs, and will signal any need for change and propose alternative solutions.
You are motivated to contribute to the ECB’s mission, to serve the citizens of the EU as a member of a public institution and to work with colleagues from all over Europe. You are keen to be part of our team and to use your skills and competencies to achieve the objectives of this position.
Further information
Traineeship of between 3 and 12 months in total.
For additional information on this specific vacancy, you can speak to Ugo Albertazzi on +49 (0)69 1344 7808 between 12:00 and 13:00 on Friday, 13 August.
Application and selection process
Further information on how to join us is available on our
website.
The recruitment process for this position will include a remote written exercise in the pre-selection phase and – if you are invited to participate in the subsequent selection phase – an online interview.
