To be filled as soon as possible, part time or full-time for up to 5 years with the option of renewal

Institute for Community Medicine - SHIP/KEF - Functional Division “Quality in the Health Sciences”

Your tasks

The position offers the opportunity to shape a distinctive research profile at the interface of epidemiology, statistical methodology, health data science, data quality, and research infrastructures based on internationally relevant cohort and health data resources.

• You will take a leading role in the scientific and strategic development of the Functional Division “Quality in the Health Sciences” and contribute to the coordination and co-leadership of its research activities
• You will contribute to and help manage major collaborative projects in the fields of epidemiology, health data science, reproducible research, FAIR data practices, and data quality in the health sciences
• You will perform and supervise advanced statistical analyses using data from large population-based studies, including the Study of Health in Pomerania (SHIP) and the German National Cohort (NAKO)
• Depending on your expertise and interests, you may contribute to additional projects, for example in the areas of incidental MRI findings or transcranial magnetic stimulation (TMS)
• You will contribute to the further methodological development of tools and workflows for reproducible statistical analysis and data quality assessment, including software-based approaches (e.g. R package dataquieR)
• You will publish in international peer-reviewed journals and contribute to the acquisition of competitive third-party funding
• You will participate in academic teaching and the supervision of junior researchers

Our requirements

• Completed university degree and doctorate in epidemiology, statistics, mathematics, biomathematics, bioinformatics, data science, psychology, life sciences, or a related field
• Strong expertise in advanced statistical analysis, ideally including longitudinal data analysis
• Excellent programming skills in R and/or Python; additional knowledge of Stata is welcome
• Experience with machine learning methods and/or generative AI approaches
• Proven experience in epidemiological or population-based health research
• Publication track record in international peer-reviewed journals
• Very good communication and presentation skills
• Very good command of English

• Acquiring or contributing to third-party funded research projects
• Administrative or routine health data
• Incidental MRI findings, pathology-related data, neurophysiological data, or transcranial magnetic stimulation (TMS)

Your Benefits

Competitive compensation and cenefits: In addition to the collective wage agreement under TV-L (classification E13 depending on personal qualifications), Universitätsmedizin Greifswald offers attractive benefits such as company pension schemes and employee discounts.
Professional development opportunities: Regular training and development programs are offered to support personal and professional growth, keeping employees up-to-date with the latest research and technology.
Interdisciplinary collaboration: Our employees have the opportunity to collaborate with leading experts from various disciplines, benefiting from an interdisciplinary approach in research and practice.
Research encouragement: Universitätsmedizin Greifswald actively supports your research projects, providing resources and infrastructure for developing innovative ideas and their implementation.
Work-Life balance: Universitätsmedizin Greifswald advocates for a balanced work-life approach, offering flexible working hours and health promotion programs like the cooperation with Hansefit GmbH. Our family office assists you with your search for accommodation and any questions related to the topic of balancing family and work.
Hanseatic location: Greifswald is a charming university town near the Baltic Sea, known for its high quality of life, diverse cultural offerings, and historically rich surroundings for work and leisure.