Jetzt bewerben: Research Associate (f/m/d) bei Friedrich Schiller Universität Jena – Arbeitsort Jena

Stellenausschreibung

Job advertisement

Vacancy ID: 090/2024
Closing date: 2024-06-02

Friedrich Schiller University is a traditional university with a strong research profile rooted in the heart of Germany. As a university covering all disciplines, it offers a wide range of subjects. Its research is focused on the areas Light—Life—Liberty. It is closely networked with non-research institutions, research companies and renowned cultural institutions. With around 18,000 students and more than 8,600 employees, the university plays a major role in shaping Jena’s character as a cosmopolitan and future-oriented city.

The Psychological Methods Division (Prof. Dr. Tobias Koch) seeks to fill the position of a

Research Associate (f/m/d)

commencing on 01.10.2024 or earlier. We offer a part-time position (75%, 30 hours per week), limited to three years (until 30. September 2027).

The position is part of the DFG project "Combining Surveys and Digital Tracking Data for Mental Health Research from a Computational Social Science Perspective (COSDIMH)".
This interdisciplinary project focuses on notable methodological challenges in measuring the relationship of mental health (MH) and digital media use (DMU). We aim to foster innovation by focusing on combining different DMU and MH measures in survey data and digital tracking data. We compare measures within and across surveys and digital tracking data to analyze their validity and reliability. We examine the short-term dynamic interaction between DMU and MH measures by combining different measures from multiple surveys and digital tracking data. Finally, we analyze the causality of the relationship between DMU and MH in an experimental setting and implement personalized interventions. We identify best practices, methods, and potential pitfalls for such combinatorial research approaches.

The project will be conducted in close cooperation with Prof. Emese Domahidi from TU Ilmenau and GESIS and is part of the DFG Infrastructure Priority Programme “New Data Spaces for the Social Sciences” (SPP 2431).

Your responsibilities:

• Participation in an interdisciplinary DFG project and collaboration with various cooperation partners
• Literature research and elaboration of the state of research on measuring the relationship of MH and DMU
• Conception and implementation of surveys and digital tracking studies
• Collaboration in data collection, data cleaning and data analysis in the project
• Preparation of and collaboration on conference participation and proceedings as well as journal publications
• Support of the department in administrative tasks related to the project
• Organization of workshops and collaboration in science communication related to the project

• Excellent master’s in social sciences (i.e. Psychology, Communication Science) or a closely related discipline
• Advanced research skills and excellent knowledge of quantitative data analysis in at least one of the following areas: longitudinal data analysis, structural equation modeling, machine learning, or psychometrics
• Programming skills in R, Python or another programming language
• Fluency in German and English, written and spoken
• interest in interdisciplinary cooperation
• Ideally, knowledge of computational social science methods, e.g. computational text analysis
• independent and responsible way of working, communication skills and the ability to work in a team

• Participation in an innovative and interdisciplinary research project.
• Responsible, interesting, and varied tasks with diverse design opportunities.
• Opportunity for a publication-based Ph.D., dedicated supervision with relevant content and methodological expertise (Prof. Dr. Tobias Koch, Prof. Dr. Emese Domahidi).
• Integration into a supportive, well-organized, and internationally connected team.
• Excellent equipment and infrastructure
• A comprehensive further and continuing education programme and individual qualification and development measures
• Attractive fringe benefits, e.g. capital formation benefits (VL) and an occupational pension (VBL)
• Remuneration based on the provisions of the Collective Agreement for the Public Sector of the Federal States (TV-L) up to salary scale 13 — depending on the candidate’s personal qualifications—, including a special annual payment in accordance with the collective agreement.
• 30 days of vacation per calendar year plus two days off on December 24 and 31

Candidates with severe disabilities will be given preference in the case of equal qualifications and suitability.

For questions regarding the job advertisement or the project, please contact Prof. Dr. Tobias Koch at