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

Friedrich-Schiller-Universität Jena

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

Your profile:

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

We offer:

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