Research Assistant / Doctoral Student (f/m/d) – AI & Historical Data at the SAFE Research Data Center

Timeframe

70% position

Fixed-Term

fixed-term until December 31, 2028

Payment

TV-H E13

Start

July 2026

The Leibniz Institute for Financial Research SAFE - Sustainable Architecture for Finance in Europe - ) promotes scientific research, transfer work to the public and independent policy advice on all aspects relating to the structure and functioning of the financial system. It aims to contribute to strengthening a sustainable and resilient financial system that drives innovation and serves the needs of the economy and citizens. Researchers from the fields of economics, law, and political science collaborate at SAFE.

As part of a research project, we investigate the use of modern AI methods, in particular Vision Large Language Models, for the automated recognition and structuring of historical economic data.

The aim is to extend or potentially replace existing OCR-based approaches and, in particular, to significantly improve the recognition of complex layouts such as tables. As a use case, we work with the historical source “Bankenjahrbuch”, which, due to its structure, provides a challenging and highly relevant basis for evaluating modern methods.

The position is based at our institute’s Research Data Center and involves close collaboration with the Research Data Center of the University of Mannheim within the framework of BERD@NFDI and the Academy project “Financial and Corporate Research from a Long-Term Perspective”. You will work at the intersection of machine learning, data processing, and economic history, contributing to the development of new methodological approaches. The project offers the opportunity to work with unique historical data and to systematically evaluate modern AI methods in a relatively unexplored application area.

Your tasks:

Evaluate current vision-based models for text recognition and document structure understanding
Analyze and compare models with respect to accuracy and runtime performance
Create and prepare training datasets for model fine-tuning
Develop and implement fine-tuning and adaptation strategies
Compare modern approaches with existing OCR methods
Document results and contribute to scientific publications
Develop reproducible workflows and share results in line with Open Science principles

Your profile:

University degree (Master or equivalent) in computer science, data science, economics, or a related field
Interest in machine learning, especially NLP, computer vision, or multimodal models
Programming skills (especially Python) and experience working with data
Interest in experimental work, model evaluation, and methodological development
Structured and self-driven working style
Interest in combining technical work with research-oriented questions
Interest in economic history or digital methods in the social sciences is a plus
Initial experience with OCR, LLMs, or similar technologies is a plus but not required
Good English skills (written and spoken)
Good German skills are an advantage

We offer:

We offer a highly interesting role at the intersection of AI, data processing, and economic history within a dynamic, interdisciplinary research environment. You will work closely with researchers and independently develop new methodological approaches.

The position provides a high degree of flexibility and independence in shaping the research and technical approach, with a strong focus on experimentation and methodological development.

The position offers the opportunity to start a doctoral project, typically in finance, economics, or economic history. Please note that the position is fixed-term, and continuation beyond the contract period cannot be guaranteed.

Remuneration is based on the collective agreement for the public sector of the State of Hesse (TV-H) at grade E13. In addition, we offer an attractive occupational pension scheme through the German public sector pension fund (VBL).

SAFE seeks to increase the share of women in research and thus strongly encourages female scholars to apply. We are also committed to promote the inclusion of persons with disabilities and therefore invites them in particular to apply.

Interested? We look forward to receiving your online application!

Apply now until 18.06.2026 by using the button "Online Application"

**Questions?**Should you have any questions, please contact Dr. Dennis Gram via e-mail: gram@safe-frankfurt.de