Under supervision, with input from the team and with a student assistant:

• Design and implement a GenAI-assisted pipeline to extract study and case characteristics from published PDF articles using large language models.
• Develop and refine prompting strategies to reconstruct symptom trajectories from graphs embedded in scientific publications.
• Benchmark automated GenAI outputs against a high-quality manually coded reference dataset to assess accuracy and identify error patterns.
• Build an interactive Shiny application that allows researchers to inspect and validate extracted data alongside original figures.
• Present findings at a conference and contribute to an open-access paper.

• You have a master-level degree.
• You have a critical thinking level, preferably with affinity for data science, research methodology, clinical psychology, or a related field.
• You have affinity with coordinating research projects and collaborating in a team or you would like to further develop your skills in these areas.
• You can translate, under supervision and in team collaboration, a complex technical plan into concrete steps.
• You have experience with R or Python and feel comfortable working with large language models or you would like to develop your skills further in these areas.
• You ask critical questions about AI output rather than taking results at face value.
• You communicate clearly — with your colleagues, the student assistant, and in writing for a scientific audience.

We offer a stimulating and interdisciplinary working environment, with a diverse range of tasks within an inspiring organization. Working at the University of Amsterdam means working in a dynamic, independent, creative, innovative, and international environment, characterized by an open atmosphere.