Research Associate (Computer Science / Data Science) | eine Stelle als wissenschaftliche Mitarbeiterin oder wissenschaftlicher Mitarbeiter (w/m/d)

Julius-Maximilians-Universität Würzburg - Zentralverwaltung Land Bayern

Würzburg, Bayern, Deutschland
Published Dec 8, 2025
Full-time
Fixed-term

Job Summary

This role is for a Research Associate specializing in Data Science and Process Mining, working within the Institute for Clinical Epidemiology and Biometry (IKE-B) and the Institute for Medical Data Sciences (ImDS) in cooperation with the Bavarian Cancer Registry. The associate will be responsible for implementing complex data preparation processes (ETL) on large, longitudinal datasets from the Cancer Registry to facilitate process analysis. Key tasks involve applying and advancing Process Mining methods using tools like Celonis, ProM, and PM4Py, comparing these techniques with classical Machine Learning/AI, and developing research tools, dashboards, and visualizations for clinical and scientific users. This is a unique opportunity to contribute to cutting-edge clinical epidemiology and health services research within national consortia (MII, NUM), offering possibilities for further academic qualification (PhD/Habilitation) and publication in high-ranking international journals.

Required Skills

Education

Master's degree or university diploma in Computer Science, Business Informatics, Data Science, Statistics, or a comparable field with a clear focus on Process Mining, Business Process Management, or Process Analysis. Possibility for PhD or Habilitation.

Experience

  • Professional experience in Process Mining tools (e.g., Celonis, ProM, PM4Py)
  • Professional experience in data modeling, data preparation, and process visualization
  • Professional experience in analyzing complex process data (alternative requirement)
  • Experience with large longitudinal and dynamic datasets

Languages

English (Fluent)

Additional

  • Initial contract duration of 2 years. Willingness to support teaching activities and methodological consultation for medical doctoral projects. Interest in clinical research.