We at RFBerlin we are looking to employ one or two Bachelor’s students as research assistants. The position involves at least 10 hours per week at an hourly rate starting from €13,19. Working hours are flexible.

The Project

The project investigates how political institutions shape scientific discovery, research productivity, and the global mobility of academic talent. Using newly assembled global data on universities, academics, publications, patents, and political institutions from 1900 to today, the project examines how transitions between democracy and autocracy affect the production and direction of knowledge. Research assistants will support the construction and analysis of large-scale datasets at the intersection of innovation, political economy, and the economics of science. The ideal candidate should have the following skills or would be willing to learning them quickly on the job.

Required Skills

• Python: Comfortable writing scripts for data cleaning, transformation, and automation. Familiarity with pandas, numpy, and standard data-handling workflows.
• Statistics and data science fundamentals: Solid grasp of descriptive statistics, regression analysis, hypothesis testing, and a general intuition for working with real-world, messy data.
• AI agents and agentic data collection: Ability to independently design, build, and deploy AI agents for research tasks — not just use them. This includes:
  • Working fluently with LLM APIs (Anthropic, OpenAI) and frameworks such as the Claude Agent SDK, LangChain, LangGraph, or similar.
  • Designing prompts and pipelines for structured extraction, classification, and large-scale document processing.
  • Implementing tool use / function calling, multi-step reasoning workflows, and browser-using or web-navigating agents.
  • Evaluating agent outputs systematically (accuracy checks, cost monitoring, prompt iteration) and integrating human-in-the-loop validation.
  • Familiarity with retrieval-augmented generation (RAG), embeddings, and vector databases is a plus.
• Data entry and hand-checking: Careful manual data entry from PDFs, scans, images, and other documents. Willingness and patience to validate automated extractions against source material, spot-check large datasets, cross-reference entries across sources, and perform manual coding or classification tasks where automation falls short. Strong attention to detail is essential.
• Data analysis: Experience working independently with a dataset — from raw input through cleaning, exploration, and presentation of results.
• Data visualization (static): Ability to produce clear, publication-quality figures using matplotlib, seaborn, or Stata’s graph commands.
• Reliability and documentation: Ability to document code clearly, organize files sensibly, and produce reproducible workflows.

Preferred / Nice to have Skills

• Stata: Working knowledge of Stata for data preparation, merging, reshaping, and basic econometric analysis (do-files, common commands, basic programming).
• Web development for data visualization(highly valued): Ability to independently build websites or web apps that visualize collected data. This includes:
  • Front-end basics: HTML, CSS, JavaScript.
  • At least one framework or library for interactive dashboards or visualizations — e.g. React, D3.js, Plotly, Observable, Streamlit, or Dash.
  • Deploying simple sites (e.g. Vercel, Netlify, GitHub Pages, Hugging Face Spaces) so others can access the output.
• Web scraping: Experience collecting data from websites using libraries such as requests, BeautifulSoup, Selenium, or Playwright. Awareness of best practices around rate limits, robots.txt, and ethical scraping.
• Version control: Familiarity with Git and GitHub for collaborative work.
• Working language: Comfortable reading and writing technical material in English.

How to Apply

RFBerlin is an equal-opportunity employer. If you are interested in applying for this position, please submit your CV and motivation letter to Professor Fabian Waldinger at [email protected] by 5 July 2026.
In your motivation letter, please explain why you are interested in this position and how your qualifications make you a strong fit for the role.

Please feel free to contact [email protected] if you have any questions. We look forward to hearing from you!