Doctoral Position at the Statistical Methods Group of the German Institute for Employment Research

The Institute for Employment Research (IAB), the research arm of the German Federal Employment Agency (BA), is seeking one predoctoral candidate or postdoc with a background in data science, statistics, computer science or a related area. The successful applicant will work in the Statistical Methods Group (KEM) of the IAB located in Nuremberg, Germany. The position will start on June 1st (alternative dates can be negotiated) and run until May 2027. The position is full-time (39 hours per week). The IAB strongly encourages continuing education and the conducted research can be part of a planned Ph.D. thesis for a predoctoral student. Teaching opportunities are possible, but teaching is not required for the position.

The Statistical Methods group is constantly working on improving the quality of the data collected and used at the IAB. Based on this mission, KEM will increasingly invest in collecting and cleaning data from alternative data sources in the upcoming years. This could be information scraped from the internet but also unstructured data from the business processes of the German Federal Employment Agency. Potential candidates are expected to support the KEM team in setting up the infrastructure required for this endeavor. The project will offer various opportunities to conduct methodological research on machine learning methods for unstructured data and on questions of selectivity of alternative data sources.

The position will encompass the following tasks and duties:
  • Implementing web scraping routines
  • Developing dashboards for data visualizations in real time
  • Integrating data from APIs
  • Implementing text mining tools (e.g. LLMs) to turn text files into structured information
  • Conducting research on the quality of the collected data
  • International presentations and preparation of manuscripts for publication in academic journals.
  • Planning and implementation of complex projects, concepts, models or methods within the department.
  • Steering and monitoring of relevant research processes within the department.
  • Optional: initiating and leading (sub)projects.

Applicants must have a master's degree or PhD in data science, statistics, computer science, social science, mathematics or an allied scientific discipline, substantive knowledge in empirical research methods, sound knowledge of statistical analyses, good programming skills in Python and/or R, a high level of self-reliance, and excellent verbal and written communication skills in English (German a plus). Knowledge in web scraping and text mining is a plus, but not required. Full health care coverage is provided according to the German public health care insurance system.

Interested candidates should send (1) a cover letter that outlines their interest and suitability for the proposed research project, including how they meet the above selection criteria, their career goals, and academic qualifications; and (2) a CV that lists educational background, relevant work experience, and publications (if any). Questions about the positions may be sent to Joerg Drechsler at

The deadline for applications is 2024/04/28. Review of applications begins as they are received and continues until the position is filled. The official job description and application submission portal (in German) can be found at

Please reference the following job number in your application:

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